Distributed UIMA Cluster Computing

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Part IDUCC Concepts

Chapter 1DUCC Overview

1.1 What is DUCC?

DUCC stands for Distributed UIMA Cluster Computing. DUCC is a cluster management system providing
tooling, management, and scheduling facilities to automate the scale-out of applications written to the UIMA
framework.

Core UIMA provides a generalized framework for applications that process unstructured information such as human
language, but does not provide a scale-out mechanism. UIMA-AS provides a scale-out mechanism to distribute UIMA
pipelines over a cluster of computing resources, but does not provide job or cluster management of the resources.
DUCC defines a formal job model that closely maps to a standard UIMA pipeline. Around this job model
DUCC provides cluster management services to automate the scale-out of UIMA pipelines over computing
clusters.

1.2 DUCC Job Model

The Job Model defines the steps necessary to scale-up a UIMA pipeline using DUCC. The goal of DUCC is to
scale-up any UIMA pipeline, including pipelines that must be deployed across multiple machines using shared
services.

The DUCC Job model consists of standard UIMA components: a Collection Reader (CR), a CAS Multiplier (CM),
application logic as implemented one or more Analysis Engines (AE), and a CAS Consumer (CC).

The Collection Reader builds input CASs and forwards them to the UIMA pipelines. In the DUCC model, the CR is run in a
process separate from the rest of the pipeline. In fact, in all but the smallest clusters it is run on a different physical machine
than the rest of the pipeline. To achieve scalability, the CR must create very small CASs that do not contain application
data, but which contain references to data; for instance, file names. Ideally, the CR should be runnable in a process
not much larger than the smallest Java virtual machine. Later sections demonstrate methods for achieving
this.

Each pipeline must contain at least one CAS Multiplier which receives the CASs from the CR. The CMs encapsulate the
knowledge of how to receive the data references in the small CASs received from the CRs and deliver the referenced data to
the application pipeline. DUCC packages the CM, AE(s), and CC into a single process, multiple instances of which are then
deployed over the cluster.

A DUCC job therefore consists of a small specification containing the following items:

The name of a resource containing the CR descriptor.

The name of a resource containing the CM descriptor.

The name of a resource containing the AE descriptor.

The name of a resource containing the CC descriptor.

Other information required to parameterize the above and identify the job such as log directory, working
directory, desired scale-out, classpath, etc. These are described in detail in subsequent sections.

On job submission, DUCC creates a single process executing the CR and one or more processes containing the analysis
pipeline.

DUCC provides other facilities in support of scale-out:

The ability to reserve all or part of a node in the cluster.

Automated management of services required in support of jobs.

The ability to schedule and execute arbitrary processes on nodes in the cluster.

Debugging tools and support.

A web server to display and manage work and cluster status.

A CLI and a Java API to support the above.

1.3 DUCC From UIMA to Full Scale-out

In this section we demonstrate the progression of a simple UIMA pipeline to a fully scaled-out job running under
DUCC.

UIMA Pipelines
A normal UIMA pipeline contains a Collection Reader (CR), one or more Analysis Engines (AE) connected in a pipeline, and
a CAS Consumer (CC) as shown in Figure 1.1.

Figure 1.1: Standard UIMA Pipeline

UIMA-AS Scaled Pipeline
With UIMA-AS the CR is separated into a discrete process and a CAS Multiplier (CM) is introduced into the pipeline as an
interface between the CR and the pipeline, as shown in Figure 1.2 below. Multiple pipelines are serviced by the CR and are
scaled-out over a computing cluster. The difficulty with this model is that each user is individually responsible for finding and
scheduling computing nodes, installing communication software such as ActiveMQ, and generally managing the distributed
job and associated hardware.

Figure 1.2: UIMA Pipeline As Scaled by UIMA-AS

UIMA Pipeline Scaled By DUCC
DUCC is a UIMA and UIMA-AS-aware cluster manager. To scale out work under DUCC the developer tells DUCC what
the parts of the application are, and DUCC does the work to build the scale-out via UIMA/AS, to find and
schedule resources, to deploy the parts of the application over the cluster, and to manage the jobs while it
executes.

On job submission, the CR is wrapped with a DUCC main class and launched as a Job Driver (or JD). The DUCC main
class establishes communication with other DUCC components and instantiates the CR. If the CR initializes
successfully, and indicates that there are greater than 0 work items to process, the specified CM, AE and CC
components are assembled into an aggregate, wrapped with a DUCC main class, and launched as a Job Process (or
JP).

The JP will replicate the aggregate as many times as specified, each aggregate instance running in a single thread. When the
aggregate initializes, and whenever an aggregate thread needs work, the JP wrapper will fetch the next work item from the
JD, as shown in Figure 1.3 below.

Figure 1.3: UIMA Pipeline As Automatically Scaled Out By DUCC

UIMA Pipeline with User-Supplied DD Scaled By DUCC
Application programmers may supply their own Deployment Descriptors to control intra-process threading and scale-out. If a
DD is specified in the job parameters, DUCC will launch each JP with the specified UIMA-AS service instantiated in-process,
as depicted in Figure 1.4 below. In this case the user can still specify how many work items to deliver to the service
concurrently.

Figure 1.4: UIMA Pipeline With User-Supplied DD as Automatically Scaled Out By DUCC

1.4 Error Management

DUCC provides a number of facilities to assist error management:

DUCC captures exceptions in the JPs and delivers them to the Job Drivers. The JD wrappers implement logic
to enforce error thresholds, to identify and log errors, and to reflect job problems in the DUCC Web Server.
Error thresholds are configurable both globally and on a per-job basis.

Error and timeout thresholds are implemented for both the initialization phase of a pipeline and the execution
phase.

Retry-after-error is supported: if a process has a failure on some CAS after initialization is successful, the
process is terminated and all affected CASs are retried, up to some configurable threshold.

To avoid disrupting existing workloads by a job that will fail to run, DUCC ensures that JD and JP processes
can successfully initialize before fully scaling out a job.

Various error conditions encountered while a job is running will prevent a problematic job from continuing
scale out, and can result in termination of the job.

1.5 Cluster and Job Management

DUCC supports management of multiple jobs and multiple users in a distributed cluster:

Multiple User Support

When properly configured, DUCC runs all work under the identity of the submitting
user. Logs are written with the user’s credentials into the user’s file space designated at job submission.

Fair-Share Scheduling

DUCC provides a Fair-Share scheduler to equitably share resources among multiple users.
The scheduler also supports semi-permanent reservation of machines.

Service Management

DUCC provides a Service Manager capable of automatically starting, stopping, and
otherwise managing and querying both UIMA-AS and non-UIMA-AS services in support of jobs.

Job Lifetime Management and Orchestration

DUCC includes an Orchestrator to manage the lifetimes of all
entities in the system.

Node Sharing

DUCC allocates processes for one or more users on a node, each with a specified amount of memory.
DUCC’s preferred mechanism for constraining memory use is Linux Control Groups, or CGroups. For nodes
that do not support CGroups, DUCC agents monitor RAM use and kill processes that exceed their share size
by a settable fudge factor.

DUCC Agents

DUCC Agents manage each node’s local resources and all processes started by DUCC. Each node in a
cluster has exactly one Agent. The Agent

Patrols the node for “foreign” (non-DUCC) processes, reporting them to the Web Server, and optionally
reaping them.

Ensures job processes do not exceed their declared memory requirements through the use of Linux
CGroups.

DUCC Web server

DUCC provides a web server displaying all aspects of the system:

All jobs in the system, their current state, resource usage, etc.

All reserved resources and associated information (owner, etc.), including the ability to request and cancel
reservations.

All services, including the ability to start, stop, and modify service definitions.

All nodes in the system and their status, usage, etc.

The status of all DUCC management processes.

Access to documentation.

Cluster Management Support

DUCC provides system management support to:

Start, stop, and query full DUCC systems.

Start, stop, and quiesce individual DUCC components.

Add and delete nodes from the DUCC system.

Discover DUCC processes (e.g. after partial failures).

Find and kill errant job processes belonging to individual users.

Monitor and display inter-DUCC messages.

1.6 Security Measures

The following DUCC security measures are provided:

user credentials

DUCC instantiates user processes using a setuid root executable named ducc_ling. See more at
ducc_ling.

command line interface

The CLI employs HTTP to send requests to the DUCC controller. The CLI creates and
employs public and private security keys in the user’s home directory for authentication of HTTP requests.
The controller validates requests via these same security keys.

webserver

The webserver facilitates operational control and therefore authentication is desirable.

Each user has the ability to control certain aspects of only his/her active submissions.

Each administrator has the ability to control certain aspects of any user’s active submissions, as well as
modification of some DUCC operational characteristics.

A simple interface is provided so that an installation can plug-in a site specific authentication mechanism comprising
userid and password.

ActiveMQ

DUCC uses ActiveMQ for administrative communication. AMQ authentication is used to prevent arbitrary
processes from participating. But when testing DUCC on a simulated cluster the AMQ broker runs without any access
restrictions so that it can be used as an application broker for UIMA-AS services used in simulation tests. See
start_sim.

1.6.1 ducc_ling

ducc_ling contains the following functions, which the security-conscious may verify by examining the source in
$DUCC_HOME/duccling. All sensitive operations are performed only AFTER switching userids, to prevent unauthorized
root access to the system.

Changes it’s real and effective userid to that of the user invoking the job.

Optionally redirects its stdout and stderr to the DUCC log for the current job.

Optionally redirects its stdio to a port set by the CLI, when a job is submitted.

“Nice”s itself to a “worse” priority than the default, to reduce the chances that a runaway DUCC job could
monopolize a system.

Optionally sets user limits.

Prints the effective limits for a job to both the user’s log, and the DUCC agent’s log.

Changes to the user’s working directory, as specified by the job.

Optionally establishes LD_LIBRARY_PATH for the job from the environment variable DUCC_LD_LIBRARY_PATH
if set in the DUCC job specification. (Secure Linux systems will prevent LD_LIBRARY_PATH from being set
by a program with root authority, so this is done AFTER changing userids).

ONLY user ducc may use the ducc_ling program in a privileged way. Ducc_ling contains checks to prevent even
user root from using it for privileged operations.

1.7 Security Issues

The following DUCC security issues should be considered:

submit transmission ’sniffed’

In the event that the DUCC submit command is ’sniffed’ then the user
authentication mechanism is compromised and user masquerading is possible. That is, the userid encryption
mechanism can be exploited such that user A can submit a job pretending to be user B.

user ducc password compromised

In the event that the ducc user password is compromised then the root
privileged command ducc_ling can be used to become any other user except root.

user root password compromised

In the event that the root user password is compromised DUCC provides no
protection. That is, compromising the root user is equivalent to compromising the DUCC user password.

Chapter 2Glossary

Agent

DUCC Agent processes run on every node in the system. The Agent receives orders to start and stop processes
on each node. Agents monitors nodes, sending heartbeat packets with node statistics to interested components
(such as the RM and web-server). If CGroups are installed in the cluster, the Agent is responsible for managing
the CGroups for each job process. All processes other than the DUCC management processes are are managed
as children of the agents.

Autostarted Service

An autostarted service is a registered service that is started automatically by DUCC when
the DUCC system is booted.

Dependent Service or Job

A dependent service or job is a service or job that specifies one or more service
dependencies in their job specification. The service or job is dependent upon the referenced service being
operational before being started by DUCC.

DUCC

Distributed UIMA Cluster Computing.

DUCC-MON

DUCC-MON is the DUCC web-server.

Job

A DUCC job consists of the components required to deploy and execute a UIMA pipeline over a computing
cluster. It consists of a JD to run the Collection Reader, a set of JPs to run the UIMA AEs, and a Job
Specification to describe how the parts fit together.

Job Driver (JD)

The Job Driver is a thin wrapper that encapsulates a Job’s Collection Reader. The JD executes
as a process that is scheduled and deployed by DUCC.

Job Process (JP)

The Job Process is a thin wrapper that encapsulates a job’s pipeline components. The JP
executes in a process that is scheduled and deployed by DUCC.

Job Specification

The Job Specification is a collection of properties that describe work to be scheduled and
deployed by DUCC. It identifies the UIMA components (CR, AE, etc) that comprise the job and the system-wide
properties of the job (CLASSPATHs, RAM requirements, etc).

Machine

A physical computing resource managed by the DUCC Resource Manager.

Node

See Machine.

Orchestrator (OR)

The Orchestrator manages the life cycle of all entities within DUCC.

Process

A process is one physical process executing on a machine in the DUCC cluster. DUCC jobs are comprised
of one or more processes (JDs and JPs). Each process is assigned one or more shares by the DUCC scheduler.

Process Manager (PM)

The Process Manager coordinates distribution of work among the Agents.

Registered Service

A registered service is a service that is registered with DUCC. DUCC saves the service
specification and fully manages the service, insuring it is running when needed, and shutdown when not.

Resource Manager (RM)

The Resource Manager schedules physical resources for DUCC work.

Service Endpoint

In DUCC, the service endpoint provides a unique identifier for a service. In the case of UIMA-AS
services, the endpoint also serves as a well-known address for contacting the service.

Service Instance

A service instance is one physical process which runs a CUSTOM or UIMA-AS service. UIMA-AS
services are usually scaled-out with multiple instances implementing the same underlying service logic.

Service Manager (SM)

The Service Manager manages the life-cycles of UIMA-AS and CUSTOM services. It
coordinates registration of services, starting and stopping of services, and ensures that services are available
and remain available for the lifetime of the jobs.

Share Quantum

The DUCC scheduler abstracts the nodes in the cluster as a single large conglomerate of resources:
memory, processor cores, etc. The scheduler logically decomposes the collection of resources into some number
of equal-sized atomic units. Each unit of work requiring resources is apportioned one or more of these atomic
units. The smallest possible atomic unit is called the share quantum, or simply, share.

Weighted Fair Share

A weighted fair share calculation is used to apportion resources equitably to the outstanding
work in the system. In a non-weighted fair-share system, all work requests are given equal consideration to all
resources. To provide some (“more important”) work more than equal resources, weights are used to bias the
allotment of shares in favor of some classes of work.

Work Items

A DUCC work item is one unit of work to be completed in a single DUCC process. It is usually
initiated by the submission of a single CAS from the JD to one of the JPs. It could be thought of as a single
“question” to be answered by a UIMA analytic, or a single “task” to complete. Usually each DUCC JP executes
many work items per job.

$DUCC_HOME

The root of the installed DUCC runtime, e.g. /home/ducc/ducc_runtime. It need not be set in
the environment, although the examples in this document assume that it has been.

Part IIDucc Users Guide

Chapter 3Command Line Interface

Overview
The DUCC CLI is the primary means of communication with DUCC. Work is submitted, work is canceled, work is
monitored, and work is queried with this interface.

All parameters may be passed to all the CLI commands in the form of Unix-like “long-form” (key, value) pairs, in which the
key is proceeded by the characters “--”. As well, the parameters may be saved in a standard Java Properties file, without
the leading “--” characters. Both a properties file and command-line parameters may be passed to each CLI.
When both are present, the parameters on the command line take precedence. Take, for example the following
simple job properties file, call it 1.job, where the environment variable “DH” has been set to the location of
$DUCC_HOME.

3.2 Operating System Limit Support

The CLI supports specification of operating system limits applied to the various job processes. To specify a limit, pass the
name of the limit and its value in the environment specified in the job. Limits are named with the string
“DUCC_RLIMIT_name” where “name” is the name of a specific limit. Supported limits include:

DUCC_RLIMIT_CORE

DUCC_RLIMIT_CPU

DUCC_RLIMIT_DATA

DUCC_RLIMIT_FSIZE

DUCC_RLIMIT_MEMLOCK

DUCC_RLIMIT_NOFILE

DUCC_RLIMIT_NPROC

DUCC_RLIMIT_RSS

DUCC_RLIMIT_STACK

DUCC_RLIMIT_AS

DUCC_RLIMIT_LOCKS

DUCC_RLIMIT_SIGPENDING

DUCC_RLIMIT_MSGQUEUE

DUCC_RLIMIT_NICE

DUCC_RLIMIT_STACK

DUCC_RLIMIT_RTPRIO

See the Linux documentation for details on the meanings of these limits and their values.

For example, to set the maximum number of open files allowed in any job process, specify an environment similar to this
when submitting the job:

ducc_submit .... --environment="DUCC_RLIMIT_NOFILE=1024" ...

3.3 Command Line Forms

The Command Line Interface is provided in several forms:

1.

A wrapper script around the uima-ducc-cli.jar.

2.

Direct invocation of each command’s class with the java command.

When using the scripts the full execution environment is established silently. When invoking a command’s class directly, the
java CLASSPATH must include the uima-ducc-cli.jar, as illustrated in the wrapper scripts.

This is a script wrapper to facilitate execution of Eclipse workspaces as DUCC jobs as well as general
execution of arbitrary processes in DUCC-managed resources.

The next section describes these commands in detail.

3.5 ducc_submit

Description:
The submit CLI is used to submit work for execution by DUCC. DUCC assigns a unique id to the job and schedules it for
execution. The submitter may optionally request that the progress of the job is monitored, in which case the state of the job
as it progresses through its lifetime is printed on the console.

Run driver and pipeline in single process. If local is specified, the process is
executed on the local machine, for example, in the current Eclipse session. If remote is specified, the jobs is
submitted to DUCC as a managed reservation and run on some (presumably larger) machine allocated by
DUCC.

--attach_console

If specified, redirect remote stdout and stderr to the local submitting console.

--cancel_on_interrupt

If specified, the job is monitored and will be canceled if the submit command is
interrupted, e.g. with CTRL-C. This option always implies --wait_for_completion.

--classpath [path-string]

The CLASSPATH used for the job. If specified, this is used for both the Job Driver
and each Job Process. If not specified, the CLASSPATH of the process invoking this request is used.

--classpath_order [user-before-ducc | ducc-before-user]

OBSOLETE - ignored.

--debug

Enable debugging messages. This is primarily for debugging DUCC itself.

--description [text]

The text is any string used to describe the job. It is displayed in the Web Server. When
specified on a command-line the text usually must be surrounded by quotes to protect it from the shell. The
default is “none”.

--driver_debug [debug-port]

Append JVM debug flags to the JVM arguments to start the JobDriver in remote
debug mode. The remote process debugger will attempt to contact the specified port.

--driver_descriptor_CR [descriptor.xml]

This is the XML descriptor for the Collection Reader. This
descriptor is a resource that is searched for in the filesystem or Java classpath as described in the notes below.
(Required)

--driver_descriptor_CR_overrides [list]

This is the Job Driver collection reader configuration overrides. They are
specified as name/value pairs in a whitespace-delimited list. Example:

--driver_descriptor_CR_overrides name1=value1 name2=value2...

--driver_exception_handler [classname]

This specifies a developer-supplied exception handler for the Job Driver. It
must implement org.apache.uima.ducc.IErrorHandler or extend org.apache.uima.ducc.ErrorHandler. A built-in default
exception handler is provided.

--driver_exception_handler_arguments [argument-string]

This is a string containing arguments for the exception
handler. The contents of the string is entirely a function of the specified exception handler. If not specified, a null is
passed in. The built-in default exception handler supports an argument string of the following form (with NO embedded
blanks):

max_job_errors=15 max_timeout_retrys_per_workitem=0

Note: When used as a CLI option, the string must usually be quoted to protect it from the shell, if it contains blanks.
The built-in default exception handler supports two arguments, whose default values are shown above. The
max_job_errors limit specifies the number of work item errors allowed before forcibly terminating the job. The
max_timeout_retrys_per_workitem limit specifies the number of times each work item is retried in the event of a
time-out.

--driver_jvm_args [list]

This specifies extra JVM arguments to be provided to the Job Driver process. It is a
blank-delimited list of strings. Example:

--driver_jvm_args -Xmx100M -Xms50M

Note: When used as a CLI option, the list must usually be quoted to protect it from the shell.

--environment [env vars]

Blank-delimited list of environment variables and variable assignments. Entries will be copied
from the user’s environment if just the variable name is specified, optionally with a final ’*’ for those with the same
prefix. If specified, this is used for all DUCC processes in the job. Example:

--environment TERM=xterm DISPLAY=:1.0 LANG UIMA_*

Additional entries may be copied from the user’s environment based on the setting of ducc.submit.environment.propagated in
the global DUCC configuration ducc.properties. Note: When used as a CLI option, the environment string must usually be quoted to protect it from the
shell.

The following cause special runtime behavior. They are considered experimental and are not guaranteed to be effective
from release to release.

DUCC_USER_CP_PREPEND [path-to-ducc-jars-and-classes]

If specified, this path is used to supply the DUCC classes required for running the Job Driver and Job
Process(es), normally set to $DUCC_HOME/lib/uima-ducc/users/*.

DUCC_WORK_ITEM_PERFORMANCE [true]

If specified, DUCC will create subdirectory work-item-performance in the user specified log directory and
will place an individual json.gz file for each work item successfully processed comprising its performance
breakdown.

DUCC_KEEP_TEMPORARY_DESCRIPTORS [true]

If specified, DUCC will not delete any temporary descriptors it creates (these are usually deleted when
the process ends.) DUCC may make a local file copy if the descriptor is in a jar, or if the filesystem is not
shared.

--help

Prints the usage text to the console.

--jvm [path-to-java]

States the JVM to use. If not specified, the same JVM used by the Agents is used. This is the full
path to the JVM, not the JAVA_HOME. Example:

--jvm /share/jdk1.6/bin/java

--log_directory [path-to-log-directory]

This specifies the path to the directory for the user logs. If not fully specified
the path is made relative to the value of the --working_directory. If omitted, the default is $HOME/ducc/logs.
Example:

--log_directory /home/bob

Within this directory DUCC creates a sub-directory for each job, using the unique numerical ID of the job. The format
of the generated log file names as described here. Note: The --log_directory specifies only the path to a directory where logs are to be stored. In order to manage
multiple processes running in multiple machines, sub-directory and file names are generated by DUCC and may not be
directly specified.

--process_debug [debug-port]

Append JVM debug flags to the JVM arguments to start the Job Process in remote
debug mode. The remote process will start its debugger and attempt to contact the debugger (usually Eclipse) on the
specified port.

--process_deployments_max [integer]

This specifies the maximum number of Job Processes to deploy at any given
time. If not specified, DUCC will attempt to provide the largest number of processes within the constraints of
fair_share scheduling and the amount of work remaining. in the job. Example:

--process_deployments_max 66

--process_descriptor_AE [descriptor]

This specifies the Analysis Engine descriptor to be deployed in the Job
Processes. This descriptor is a resource that is searched for in the filesystem or Java classpath as described in the
notes below. It is mutually exclusive with --process_descriptor_DD. Example:

--process_descriptor_AE /home/billy/resource/AE_foo.xml

--process_descriptor_AE_overrides [list]

This specifies AE overrides. It is a whitespace-delimited list of name/value
pairs. Example:

--process_descriptor_AE_Overrides name1=value1 name2=value2

--process_descriptor_CC [descriptor]

This specifies the CAS Consumer descriptor to be deployed in the Job
Processes. This descriptor is a resource that is searched for in the filesystem or Java classpath as described in the
notes below. It is mutually exclusive with --process_descriptor_DD. Example:

--process_descriptor_CC /home/billy/resourceCCE_foo.xml

--process_descriptor_CC_overrides [list]

This specifies CC overrides. It is a whitespace-delimited list of name/value
pairs. Example:

--process_descriptor_CC_overrides name1=value1 name2=value2

--process_descriptor_CM [descriptor]

This specifies the CAS Multiplier descriptor to be deployed in the Job
Processes. This descriptor is a resource that is searched for in the filesystem or Java classpath as described in the
notes below. It is mutually exclusive with --process_descriptor_DD. Example:

--process_descriptor_CM /home/billy/resource/CM_foo.xml

--process_descriptor_CM_overrides [list]

This specifies CM overrides. It is a whitespace-delimited list of name/value
pairs. Example:

--process_descriptor_CM_overrides name1=value1 name2=value2

--process_descriptor_DD [descriptor]

This specifies a UIMA Deployment Descriptor for the job processes for
DD-style jobs. This is mutually exclusive with --process_descriptor_AE, --process_descriptor_CM, and
--process_descriptor_CC. This descriptor is a resource that is searched for in the filesystem or Java classpath as
described in the notes below. Example:

--process_descriptor_DD /home/billy/resource/DD_foo.xml

Alias: --process_DD

--process_failures_limit [integer]

This specifies the maximum number of individual Job Process (JP) failures allowed
before killing the job. The default is twenty(20). If this limit is exceeded over the lifetime of a job DUCC terminates the
entire job. Example:

--process_failures_limit 23

--process_initialization_failures_cap [integer]

This specifies the maximum number of failures during a
UIMA process’s initialization phase. If the number is exceeded the system will allow processes which are
already running to continue, but will assign no new processes to the job. The default is ninety-nine(99).
Example:

--process_initialization_failures_cap 62

Note that the job is NOT killed if there are processes that have passed initialization and are running. If this limit is
reached, the only action is to not start new processes for the job.

--process_initialization_time_max [integer]

This is the maximum time in minutes that a process is allowed to remain
in the “initializing” state, before DUCC terminates it. The error counts as an initialization error towards the
initialization failure cap.

--process_jvm_args [list]

This specifies additional arguments to be passed to all of the job processes as a
blank-delimited list of strings. Example:

--process_jvm_args -Xmx400M -Xms100M

Note: When used as a CLI option, the arguments must usually be quoted to protect them from the
shell.

--process_memory_size [size]

This specifies the maximum amount of RAM in GB to be allocated to each Job Process.
This value is used by the Resource Manager to allocate resources.

--process_per_item_time_max [integer]

This specifies the maximum time in minutes that the Job Driver will wait
for a Job Processes to process a CAS. If a timeout occurs the process is terminated and the CAS marked in error (not
retried). If not specified, the default is 24 hours. Example:

--process_per_item_time_max 60

--process_pipeline_count [integer]

This specifies the number of pipelines per process to be deployed, i.e.
the number of work-items each JP will process simultaneously. It is used by the Resource Manager to
determine how many processes are needed, by the Job Process wrapper to determine how many threads to
spawn, and by the Job Driver to determine how many CASs to dispatch. If not specified, the default is 4.
Example:

--process_pipeline_count 7

Alias: --process_thread_count

--scheduling_class [classname]

This specifies the name of the scheduling class the used to determine the resource
allocation for each process. The names of the classes are installation dependent. If not specified, the FAIR_SHARE
default is taken from the site class definitions file described here. Example:

--scheduling_class normal

--service_dependency[list]

This specifies a blank-delimited list of services the job processes are dependent upon. Service
dependencies are discussed in detail here. Example:

All the parameters used to submit a job may be placed in a standard Java properties file. This
file may then be used to submit the job (rather than providing all the parameters directory to submit). The leading --
is omitted from the keywords.

Note that properties in a specification file may be overridden by other command-line parameters, as discussed
here.

--suppress_console_log

If specified, suppress creation of the log files that normally hold the redirected stdout and
stderr.

--timestamp

If specified, messages from the submit process are timestamped. This is intended primarily for use with a
monitor with –wait_for_completion.

--wait_for_completion

If specified, the submit command monitors the job and prints periodic state and progress
information to the console. When the job completes, the monitor is terminated and the submit command returns. If the
command is interrupted, e.g. with CTRL-C, the job will not be canceled unless --cancel_on_interrupt is also
specified.

--working_directory

This specifies the working directory to be set by the Job Driver and Job Process processes. If not
specified, the current directory is used.

Notes: When searching for UIMA XML resource files such as descriptors, DUCC searches either the filesystem or Java classpath
according to the following rules:

1.

If the resource ends in .xml it is assumed the resource is a file in the filesystem and the path is either an
absolute path or a path relative to the specified working directory. [by location]

2.

If the resource does not end in .xml, it is assumed the resource is in the Java classpath. DUCC creates a
resource name by replacing the ”.” separators with ”/” and appending ”.xml”. [by name]

3.6 ducc_cancel

Description:
The cancel CLI is used to cancel a job that has previously been submitted but which has not yet completed.

Optional. This specifies the reason the job is canceled for display in the web server. Note that
the shell requires a quoted string. Example:

ducc_cancel --id 12 --reason "This is a pretty good reason."

--dpid [pid]

If specified only this DUCC process will be canceled. If not specified, then entire job will be canceled. The pid
is the DUCC-assigned process ID of the process to cancel. This is the ID in the first column of the Web Server’s job
details page, under the column labeled “Id”.

--help

Prints the usage text to the console.

--role_administrator

The command is being issued in the role of a DUCC administrator. If the user is not also a
registered administrator this flag is ignored. (This helps to protect administrators from accidentally canceling jobs they
do not own.)

Notes:
None.

3.7 ducc_reserve

Description:
The reserve CLI is used to request a reservation of resources. Reservations can be for machines based on memory
requirements. All reservations are persistent: the resources remain dedicated to the requester until explicitly returned. All
reservations are performed on an ”all-or-nothing” basis: either the entire set of requested resources is reserved, or the
reservation request fails.

All forms of ducc_reserve block until the reservation is complete (or fails) at which point the DUCC ID of the reservation and
the names of the reserved nodes are printed to the console and the command returns.

The text is any string used to describe the reservation. It is displayed in the Web Server.

--help

Prints the usage text to the console.

--memory_size [integer]

This specifies the amount of memory the reserved machine must support. After
rounding up it must match the total usable memory on the machine. (Required)

Alias: --instance_memory_size

--scheduling_class [classname]

This specifies the name of the scheduling class used to determine the resource
allocation for each process. It must be one implementing the RESERVE policy. If not specified, the RESERVE
default is taken from the site class definitions file described here.

-f, --specification [file]

All the parameters used to request a reservation may be placed in a standard Java
properties file. This file may then be used to submit the request (rather than providing all the parameters
directory to submit).

--timestamp

If specified, messages from the submit process are timestamped. This is intended primarily for use
with a monitor with –wait_for_completion.

--wait_for_completion

By default, the reserve command monitors the request and prints periodic state and
progress information to the console. When the reservation completes, the monitor is terminated and the reserve
command returns. If the command is interrupted, e.g. with CTRL-C, the request will not be canceled unless
--cancel_on_interrupt is also specified. If this option is disabled by specifying a value of “false”, the command
returns as soon as the request has been submitted.

Notes:
Reservations must be for entire machines, in a job class implementing the RESERVE scheduling policy. The default DUCC
distribution configures class reserve for entire machine reservations. A reservation request will be queued if there is no
available machine in that class matching the requested size (after rounding up), or up to ducc.rm.reserve_overage larger than
the request (after rounding up). The user may cancel the request with ducc_unreserve or with CTRL-C if
--cancel_on_interrupt was specified.

The command is being issued in the role of a DUCC administrator. If the user is not also a
registered administrator this flag is ignored. (This helps to protect administrators from inadvertently canceling
jobs they do not own.)

Notes:
None.

2y

3.9 ducc_process_submit

Description:
Use ducc_process_submit to submit a Managed Reservation, also known as an arbitrary process to DUCC. The intention of
this function is an alternative to utilities such as ssh, in order to allow the spawned processes to be fully managed by DUCC.
This allows the DUCC scheduler to allocate the necessary resources (and prevent over-allocation), and the DUCC run-time
environment to manage process lifetime.

If attach_console is specified, Stdin, Stderr, and Stdout of the remote process are redirected to the submitting
console. It is thus possible to run interactive sessions with remote processes where the resources are managed by
DUCC.

Blank-delimited list of environment variables and variable assignments. Entries will be copied
from the user’s environment if just the variable name is specified, optionally with a final ’*’ for those with the same
prefix. If specified, this is used for all DUCC processes in the job. Example:

--environment TERM=xterm DISPLAY=:1.0 LANG UIMA_*

Additional entries may be copied from the user’s environment based on the setting of ducc.submit.environment.propagated
in the global DUCC configuration ducc.properties.

Note: When used as a CLI option, the environment string must usually be quoted to protect it from the
shell.

--help

Prints the usage text to the console.

--log_directory [path-to-log directory]

This specifies the path to the directory for the user logs. If not specified, the default is $HOME/ducc/logs.
Example:

--log_directory /home/bob

Within this directory DUCC creates a sub-directory for each process, using the numerical ID of the job. The format of
the generated log file names as described here.

Note: Note that --log_directory specifies only the path to a directory where logs are to be stored. In order to manage
multiple processes running in multiple machines DUCC, sub-directory and file names are generated by DUCC and may
not be directly specified.

--process_executable [program name]

This is the full path to a program to be executed. (Required)

--process_executable_args [argument list]

This is a list of arguments for process_executable, if any.
When specified on a command-line the text usually must be surrounded by quotes to protect it from the
shell.

--process_memory_size [size]

This specifies the maximum amount of RAM in GB to be allocated to each process. This
value is used by the Resource Manager to allocate resources. if this amount is exceeded by a process the Agent
terminates the process with a ShareSizeExceeded message.

--scheduling_class [classname]

This specifies the name of the scheduling class the RM will use to determine the
resource allocation for each process. The names of the classes are installation dependent. If not specified, the
FIXED_SHARE default is taken from the site class definitions file described here.

--specification, -f [file]

All the parameters used to submit a process may be placed in a standard Java properties file.
This file may then be used to submit the process (rather than providing all the parameters directory to
submit).

If specified, suppress creation of the log files that normally hold the redirected stdout and
stderr.

--timestamp

If specified, messages from the submit process are timestamped. This is intended primarily for use with a
monitor with –wait_for_completion.

--wait_for_completion

If specified, the submit command monitors the remote process and prints periodic state and
progress information to the console. When the process completes, the monitor is terminated and the submit
command returns. If the command is interrupted, e.g. with CTRL-C, the request will not be canceled unless
--cancel_on_interrupt is also specified.

--working_directory

This specifies the working directory to be set by the Job Driver and Job Process processes. If not
specified, the current directory is used.

Notes:

3.10 ducc_process_cancel

Description:
The cancel CLI is used to cancel a process that has previously been submitted but which has not yet completed.

Optional. This specifies the reason the process is canceled, for display in the web server.

--role_administrator

The command is being issued in the role of a DUCC administrator. If the user is not also a
registered administrator this flag is ignored. (This helps to protect administrators from inadvertently canceling
work they do not own.)

Notes:
None.

3.11 ducc_services

Description:
The ducc_services CLI is used to manage service registration. It has a number of functions as listed below.

The functions include:

Register

This registers a service with the Service Manager by saving a service specification in the Service Manager’s
registration area. The specification is retained by DUCC until it is unregistered.

The registration consists primarily of a service specification, similar to a job specification. This specification
is used when the Service Manager needs to start a service instance. The registered properties for a service are
made available for viewing from the DUCC Web Server’s service details page.

Unregister

This unregisters a service with the Service Manager. When a service is unregistered DUCC stops the
service instance and moves the specification to history.

Start

The start function instructs DUCC to allocate resources for a service and to start it in those resources. The
service remains running until explicitly stopped. DUCC will attempt to keep the service instances running if
they should fail. The start function is also used to increase the number of running service instances if desired.

Stop

The stop function stops some or all service instances.

Modify

The modify function allows most aspects of a registered service to be updated without re-registering the
service. Where feasible the modification takes place immediately; otherwise the service must be stopped and
restarted.

Disable

This prevents additional instances of a service from being spawned. Existing instances are not affected.

Enable

This reverses the effect of a manual disable command or an automatic disable of the service due to excessive
errors.

Ignore References

A reference started service no longer exits after the last work referencing the service exits. It
remains running until a manual stop is performed.

Observe References

A manually started service is made to behave like a reference-started service and will
terminate after the last work referencing the service has exited (plus the configured linger time).

Query

The query function returns detailed information about all known services, both registered and otherwise.

3.11.2 ducc_services –register [specification file] [options]

The register function submits a service specification to DUCC. DUCC stores this information until it is unregistered. Once
registered, a service may be started, stopped, etc.

The specification file is optional. If designated, it is a Java properties file containing other registration options, minus the
leading “–”. If both a specification file and command-line options are designated, the command-line options override those in
the specification.

The options describing the service include:

--autostart [true or false]

This indicates whether to register the service as an autostarted service. If not
specified, the default is false.

--classpath [path-string]

The CLASSPATH used for the service, if the service is a UIMA-AS services. If not
specified, the CLASSPATH of the process invoking this request is used.

--classpath_order [user-before-ducc | ducc-before-user]

OBSOLETE - ignored.

--debug

Enable debugging messages. This is primarily for debugging DUCC itself.

--description [text]

The text is any quoted string used to describe the job. It is displayed in the Web Server.

Note: When used as a CLI option, the description string must usually be quoted to protect it from the shell.

--environment [env vars]

Blank-delimited list of environment variables and variable assignments for the service. Entries
will be copied from the user’s environment if just the variable name is specified, optionally with a final ’*’ for those
with the same prefix. Example:

--environment TERM=xterm DISPLAY=:1.0 LANG UIMA_*

Additional entries may be copied from the user’s environment based on the setting of

ducc.submit.environment.propagated

in the global DUCC configuration ducc.properties.

Note: When used as a CLI option, the environment string must usually be quoted to protect it from the
shell.

--help

This prints the usage text to the console.

--instances [n]

This specifies the number of instances to start when the service is started. If not specified, the default is 1.
Each instance has the DUCC_SERVICE_INSTANCE environment variable set to a unique sequence number, starting
from 0. If an instabce is restarted it will be assigned the same number.

--instance_failures_window [time-in-minutes]

This specifies the time in minutes that service instance
failures are tracked. If there are more service instance failures within this time period than are allowed by
--instance_failures_limit the service’s autostart flag is set to false and the Service Manager no longer starts instances
for the service. The instance failures may be reset by resetting the autostart flag with the --modify option, or if no
subsequent failures occur within the window.

This option pertains only to failures which occur after the service is initialized.

This value is managed the a services ping/monitor. Thus if it is dynamnically changed with the --modify option it
takes effect immediately.

--instance_failures_limit [number of allowable failures]

This specifies the maximum number of service failures
which may occur with the time specified by --instance_failures_window before the Service Manager disables the
service’s autostart flag. The accounting of failures may be reset by resetting the autostart flag with the --modify
option or if no subsequent failures occur within the time window.

This option pertains only to failures which occur after the service is initialized.

This value is managed the a services ping/monitor. Thus if it is dynamnically changed with the --modify option the
current failure counter is reset and the new value takes effect immediately.

--instance_init_failures_limit [number of allowable failures]

This specifies the number of consecutive
failures allowed while a service is in initialization state. If the maximum is reached, the service’s autostart
flag is turned off. The accounting may be reset by reeenabling autostart, or if a successful initialization
occurs.

--jvm [path-to-java]

This specifies the JVM to use for UIMA-AS services. If not specified, the same JVM used by the
Agents is used.

Note: The path must be the full path the the Java executable (not simply the JAVA_HOME environment variable.).
Example:

--jvm /share/jdk1.6/bin/java

--process_jvm_args [list]

This specifes extra JVM arguments to be provided to the server process for UIMA-AS
services. It is a blank-delimited list of strings. Example:

--process_jvm_args -Xmx100M -Xms50M

Note: When used as a CLI option, the argument string must usually be quoted to protect it from the
shell.

--log_directory [path-to-log directory]

This specifies the path to the directory for the individual service instance logs.
If not specified, the default is $HOME/ducc/logs. Example:

--log_directory /home/bob

Within this directory DUCC creates a subdirectory for each job, using the numerical ID of the job. The format of the
generated log file names as described here.

Note: Note that --log_directory specifies only the path to a directory where logs are to be stored. In order to manage
multiple processes running in multiple machines DUCC, sub-directory and file names are generated by DUCC and may
not be directly specified.

The specifies a debug port that a service instance connects to when it is started. If
specified, only a single service instance is started by the Service Manager regardless of the number of instances
specified. The service instance’s JVM options are enhanced so the service instance starts in debug mode with the
correct call-back host and port. The host and port are used for the callback.

To disable debugging, user the --modify service option to set the host:port to the string “off”.

--process_executable [program-name]

For CUSTOM services, this specifies the full path of the program to
execute.

This specifies the maximum amount of RAM in GB to be allocated to each Job Process.
This value is used by the Resource Manager to allocate resources.

--scheduling_class [classname]

This specifies the name of the scheuling class the RM will use to determine the resource
allocation for each process. The names of the classes are installation dependent. If not specified, the FIXED_SHARE
default is taken from the site class definitions file described here.

--service_dependency[list]

This specifies a blank-delimited list of services the job processes are dependent upon. Service
dependencies are discussed in detail here. Example:

Note: When used as a CLI option, the list must usually be quoted to protect it from the shell.

--service_linger [milliseconds]

This is the time in milliseconds to wait after the last referring job or service exits before
stopping a non-autostarted service.

--service_ping_arguments [argument-string]

This is any arbitrary string that is passed to the init() method of the
service pinger. The contents of the string is entirely a function of the specific service. If not specified, a null is passed
in.

Note: When used as a CLI option, the string must usually be quoted to protect it from the shell, if it contains
blanks.

The build-in default UIMA-AS pinger supports an argument string of the following form (with NO embedded
blanks):

service_ping_arguments=broker-jmx-port=pppp,meta-timeout=tttt

The keywords in the string have the following meaning:

broker-jmx-port=pppp

This is the JMX port for the service’s broker. If not specified, the default of 1099
is used. This is used to gather ActiveMQ statistics for the service.

Sometimes it is necessary to disable the gathering of ActiveMQ statistics through JMX; for example, if
the queue is accessed via HTTP instead of TCP. To disable JMX statistics, specify the port as
“none”.

service_ping_arguments=broker-jmx-port=none

meta-timeout=tttt

This is the time, in milliseconds, to wait for a response to UIMA-AS get-meta. If not specified,
the default is 5000 milliseconds.

--service_ping_class [classname]

This is the Java class used to ping a service.

This parameter is required for CUSTOM services.

This parameter may be specified for UIMA-AS services; however, DUCC supplies a default pinger for UIMA-AS
services.

--service_ping_classpath [classpath]

If service_ping_class is specified, this is the classpath containing
service_custom_ping class and dependencies. If not specified, the Agent’s classpath is used (which will generally be
incorrect.)

--service_ping_dolog [true or false]

If specified, write pinger stdout and stderr messages to a log, else suppress the log.
See Service Pingers for details.

--service_ping_jvm_args [string]

If service_ping_class is specified, these are the arguments to pass to jvm when
running the pinger. The arguments are specified as a blank-delimited list of strings. Example:

--service_ping_jvm_args -Xmx400M -Xms100M

Note: When used as a CLI option, the arguments must usually be quoted to protect them from the
shell.

--service_ping_timeout [time-in-ms]

This is the time in milliseconds to wait for a ping to the service. If the timer
expires without a response the ping is “failed”. After a certain number of consecutive failed pings, the service is
considered “down.” See Service Pingers for more details.

--service_request_endpoint [string]

This specifies the expected service id.

This string is optional for UIMA-AS services; if specified, however, it must be of the form UIMA-AS:queue:broker-url,
and both the queue and broker must match those specified in the service DD specifier.

If the service is CUSTOM, the endpoint is required, and must be of the form CUSTOM:string where the contents of the
string are determined by the service.

--working_directory [directory-name]

This specifies the working directory to be set for the service processes. If not
specified, the current directory is used.

3.11.3 ducc_services –start options

The start function instructs DUCC to allocate resources for a service and to start it in those resources. The service remains
running until explicitly stopped. DUCC will attempt to keep the service instances running if they should fail. The start
function is also used to increase the number of running service instances if desired.

--start [service-id or endpoint]

This indicates that a service is to be started. The service id is either the numeric ID
assigned by DUCC when the service is registered, or the service endpoint string. Example:

This is the number of instances to start. If omitted, sufficient instances to match the registered
number are started. If more than the registered number of instances is running this command has no
effect.

If the number of instances is specified, the number is added to the currently number of running instances. Thus if five
instances are running and

ducc_services --start 33 --instances 5

is issued, five more service instances are started for service 33 for a total of ten, regardless of the number specified in
the registration.

This is the number of instances to stop. If omitted, all instances for the service are stopped. If the
number of instances is specified, then only the specified number of instances are stopped. Thus if ten instances are
running for a service with numeric id 33 and

ducc_services --stop 33 --instances 5

is issued, five (randomly selected) service instances are stopped for service 33, leaving five running. The
registered number of instances is never reduced to zero even if the number of running instances is reduced to
zero.

3.11.7 ducc_services –observe_references options

If the service is not autostarted and has active instances, this instructs the Service Manager to track references
to the service, and when the last referencing service exits, stop all instances. The registered linger time is
observed after the last reference exits before stopping the service. See the management policy section for more
information.

--observe_references [service-id or endpoint]

Instructs the SM to manage the service as a reference-started service.
Example:

3.11.8 ducc_services –ignore_references options

If the service is manually started and has active instances, this instructs the Service Manager to NOT stop the service when
the last referencing job has exited. It transforms a manually-started service into a reference-started service. See the
management policy section for more information.

--ignore_references [service-id or endpoint]

Instructs the SM to manage the service as a reference-started service.
Example:

3.11.9 ducc_services –modify options

The modify function dynamically updates some of the attributes of a registered service. All service options as
described under --register other than the service_endpoint and process_descriptor_DD may be modified wihtout
re-registering the service. In most cases the service will need to be stopped and restarted for the update to
apply.

The modify option is of the following form:

--modify [service-id or endpoint]

This identifies the service to modify. The service id is either the numeric ID assigned
by DUCC when the service is registered, or the service endpoint string. Example:

The following modifications take place immediately without the need to restart the service:

instances

autostart

service_linger

process_debug

instance_init_failures_limit

Modifying the following registration options causes the service pinger to be stopped and started, without affecting any of the
service instances themselves. The pinger is restarted even if the modification value is the same as the old value. (A good way
to restart a possibly errant pinger is to modify it’s service_ping_dolog from “true” to “true” or from “false” to
“false”.)

service_ping_arguments

service_ping_class

service_ping_classpath

service_ping_jvmargs

service_ping_timeout

service_ping_dolog

3.11.10 ducc_services –query options

The query function returns details about all known services of all types and classes, including the DUCC ids of the service
instances (for submitted and registered services), the DUCC ids of the jobs using each service, and a summary of each
service’s queue and performance statistics, when available.

All information returned by ducc_services --query is also available via the Services Page of the Web Server as well as the
DUCC Service API (see the JavaDoc).

--query [service-id or endpoint]

This indicates that a service is to be stopped. The service id is either the
numeric ID assigned by DUCC when the service is registered, or the service endpoint string.

If no id is given, information about all services is returned.

Below is a sample service query.

The service with endpoint UIMA-AS:FixedSleepAE_5:tcp://bobmach:61617 is a registered service, whose
registered numeric id is 2. It was registered by bob for two instances and no autostart. Since it is not autostarted,
it will be terminated when it is no longer used. It will linger for 5 seconds after the last referencing job completes,
in case a subsequent job that uses it enters the system (not a realistic linger time!). It has two active instances
whose DUCC Ids are 9 and 5. It is currently used (referenced) by DUCC jobs 1 and 5.

3.12 viaducc and java_viaducc

Description:
Viaducc is a small script wrapper around the ducc_process_submit CLI to facilitate launching processes on DUCC-managed
machines, either from the command line or from an Eclipse run configuration.

When run from the command line as “viaducc”, the arguments are bundled into the form expected by ducc_process_submit
and submitted to DUCC. By default the remote stdin and stdout of the deployed process are mapped back to the command
line terminal.

If a symbolic link to the viaducc script is created with the name “java_viaducc” and used from the command line, the
arguments are assumed to be a Java classname and its arguments. The java process will be executed using DUCC’s default
JRE, or optionally, a specific JRE supplied by the user with a -D argument.

If the “java_viaducc” symbolic link is installed in a JRE/bin directory, DUCC will use the java executable from
the same directory. More interestingly, it may be specified as an alternative to the “java” command in an
eclipse launcher. The remote stdin and stdout of the deployed DUCC process are redirected to the Eclipse
console. This provides essentially transparent execution of code in an Eclipse workspaces on DUCC-managed
resources.

Usage:

viaducc [defines] [command and parameters]

or

java_viaducc [defines] [java-class and parameters]

The “defines” are described below. The “command and parameters” are either any command (with full path) and it’s
arguments, or a Java class (with a “main”) and its arguments (including the classpath if necessary.)

Defines
The arguments are specified in the syntax of Java “-D” system properties, to be more consistent with execution under
Eclipse.

-DDUCC_MEMORY_SIZE

This specifies the memory required, in GB. If not specified, the smallest memory
quanta configured for the scheduler is used.

-DDUCC_CLASS

This is the scheduling class to submit the process to. It should generally be a non-preemptable
class. If not specified, it defaults to class “fixed”.

-DDUCC_ENVIRONMENT

This species additional environment parameters to pass to the job. It should specify a
quoted string of blank-delimited K=V environment values. For example:

-DDUCC_ENVIRONMENT="DUCC_RLIMIT_NOFILE=1000 V1=V2 A=B"

-DJAVA_BIN

This species the exact “java” command to use, for “java_viaducc”. It must be a full path to some JRE
that is known to be installed on all the DUCC nodes. If not specified, the JRE used to run ducc is
used.

-DDUCC_DESCRIPTION

The description string to use for the submission. If not specified, the description defaults to
the executable name, viaducc or java_viaducc.

-DDUCC_NO_CANCEL_ON_INTERRUPT

If specified this no-argument option disables automatic process
cancellation when the submitting process terminates before the remote process.

The next sections describe various tools in detail.

3.13 ducc_status

Description:
The status tool is used to obtain the status of the various DUCC daemons.

Usage:

Script

$DUCC_HOME/bin/ducc_status options

Options:

--help

Prints the usage text to the console.

--agents

Prints status of agents to the console (in addition to the head node daemons).

Chapter 4The DUCC Public API

4.1 Overview Of The DUCC API

The DUCC API provides a simple programmatic (Java) interface to DUCC for submission and cancellation of
work. (Note that the DUCC CLI is implemented using the API and provides a model for how to use the
API.)

All the API objects are instantiated using the same arguments as the CLI. The API provides three variants for supplying
arguments:

1.

An array of Java Strings, for example DuccJobSubmit(String[] args).

2.

A list of Java Strings, for example DuccJobSubmit(List<String> args).

3.

A Java Properties object, for example DuccJobSubmit(Properties args).

After instantiation of an API object, the boolean execute() method is called. This method transmits the arguments
to DUCC. If DUCC receives and accepts the args, the method returns “true”, otherwise it returns “false.
Methods are provided to retrieve relevant information when the execute() returns such as IDs, messages,
etc.

In the case of jobs and managed reservations, if the specification requested debug, console attachment, or “wait for
completion”, the API provides methods to block waiting for completion.

In the case of jobs and managed reservations, a callback object may also be passed to the constructor. The callback object
provides a means to direct messages to the API user. If the callback is not provided, messages are written to standard
output.

The API is thread-safe, so developers may manage multiple, simultaneous requests to DUCC.

Below is the “main()” method of DuccJobSubmit, demonstrating the use of the API:

4.2 Compiling and Running With the DUCC API

4.3 Java API

Chapter 5Service Management

5.1 Overview.

A DUCC service is defined by the following two criteria:

A service is one or more long-running processes that await requests and return something in response.

A service that is managed by DUCC is accompanied by a small program called a “pinger” that the DUCC
Service Manager uses to gauge the availability and health of the service. This pinger must always be be present.
DUCC will supply a default pinger for UIMA-AS services if none is specified.

Users may supply their own “pingers” by supplying a Java class that implements the pinger API. This is
referred to as a “custom” pinger in this document. There are a number of service registration options which
allow specification and parametrization of custom pingers.

The pinger API enables the following functions for custom pingers:

increase and decrease the number of service instances,

manage failure restart policies,

enable and disable service autostart,

notify the Service Manager of the date of last use of a service,

notify the Service Manager of the health and availability of a service,

returns a string for display in the DUCC Web server to show relevant service information

A service is usually a UIMA-AS service, but DUCC supports any arbitrary process as a service.

The DUCC Service Manager implements several high-level functions:

Ensure services are available for jobs before allowing the jobs to start.

Enable fast-fail for jobs which reference services which are unavailable.

Start a service when it is referenced by a job, and stop it when no longer needed.

Optionally start a service when DUCC is booted.

Insure services remain operational across failures.

Report service failures.

Run service pingers and respond to the pinger API as needed.

When work enters the system with a declared dependency on a service, one of the following actions is taken:

If the service is not registered, the work request is automatically canceled (to avoid wasting resources on a job
that is known cannot succeed.)

If the service registered but not running, the Service Manager attempts to start it; the job remains queued
until the service is started and its pinger reports good health.

If the service exists but cannot be started, the remains queued and error status is shown in the web server. Once
the service is working again the work is allowed to proceed. (Jobs already running are not directly affected,
unless they also cannot access the service.)

If the service processes are running but the pinger reports failure contacting the service, the work remains
queued with error status shown in the webserver. Once the service pinger indicates the service is functional
again the work is allowed to proceed.

5.2 Service Types.

DUCC supports two types of services: UIMA-AS and CUSTOM:

UIMA-AS

This is a normal UIMA-AS service. DUCC fully supports all aspects of UIMA-AS services with minimal
effort from developers. A default pinger is supplied by DUCC for UIMA-AS services. It is legal to define a
custom pinger for a UIMA-AS service.

CUSTOM

This is any arbitrary service. Developers must provide a custom pinger and declare the pinger in the
service registration.

DUCC also supports services that are not managed by DUCC. These are known as ping-only services. The registration for a
ping-only service contains only keywords needed to support a pinger, which communicates with the non-DUCC
service. Ping-only services must be defined as custom services; there is no default pinger provided for ping-only
services.

5.3 Service Instance IDs

DUCC 2.0.0 introduces support for constant service instance IDs. As a service is being started, the SM assigns
monotonically increasing IDs to each service instance, starting with ID 0, up the the maximum number of instances
started.

If an instance exits unexpectedly, the SM re-spawns it (unless a failure threshold has been exceeded). The new instance is
assigned the same instance ID as the instance it replaces. This insures that, for example, instance “three” is always started as
instance “three”, maintained constant over failures and SM restarts.

The instance ID is communicated to the process through the environment with the key DUCC_SERVICE_INSTANCE. This key
may also be used in service registrations if it is desired to pass the instance ID via parameters of some sort. For
example:

5.4 Service References and Endpoints

Services are identified by an entity called a service endpoint. Jobs and other services use the registered service endpoint to
indicate dependencies on specific services.

A service endpoint is of the form

<service-type>:<unique id>

The service-type must be either UIMA-AS or CUSTOM.

The unique id is any string needed to ensure the service is uniquely named. For UIMA-AS services, the unique ID must be
the same as the service endpoint specified in service’s DD XML descriptor. The UIMA-AS service endpoint is always of the
form:

queue-name:broker-url

where queue-name is the name of the ActiveMQ queue used by the service, and broker-url is the ActiveMQ broker URL.
Sample DUCC Service endpoints:

Jobs or other services may register dependencies on specific services by listing one or more service endpoints int their
specifications. See the job and services CLI descriptions for details.

A service is registered with DUCC using the ducc_services API/CLI. Service registrations are persisted by DUCC and last
over DUCC and cluster restarts.

5.5 Application Broker for UIMA-AS Services

UIMA-AS services require a separate ActiveMQ broker. An application broker can be started using a script in the UIMA-AS
distribution bundled with DUCC.

export UIMA_HOME=$DUCC_HOME/apache-uima
$UIMA_HOME/bin/startBroker.sh

This uses the default configuration of port 61616 for tcp access and 1099 for JMX access (used by the default UIMA-AS
pinger.) The internal DUCC broker uses different ports so both may run on the same node.

5.6 Service Management Policies

The Service Manager implements these policies for managing services:

Autostarted Services

An autostarted service is automatically started when the DUCC system is first booted. If
an instance should die, DUCC automatically restarts the instance and continually maintains the registered
number of service instances.

By default, to handle fatal errors in autostarted services, The Service Manager maintains a time window in
which only a specific number of instance failures may occur. If the number of failures within that window of
time is excessive DUCC will set a disabled flag and no longer restart instances. Instance which do not fail are
left running. The disabled flag must be manually reset once the problem is resolved before new instances can
be started.

The default failure policy is implemented in the service pinger.. Service owners may redefine the default policy
by supplying their own pingers for a service.

Reference-started Services

A reference-started service is a registered service that is started only when referenced
by another job or service. If the service is already started, the dependent job/service is marked “Services
Available” and can be scheduled.. If not, the service registry is checked and if a matching enabled service is
found, it is started by DUCC. While the service is being started, jobs are held “Waiting For Services” to ensure
the service is viable. Once the service has completed initialization and the pinger indicates it is viable, all work
waiting on it is then marked “Services Available” and started.

To handle fatal errors in reference-started services, The Service Manager maintains a time window in which
only a specific number of instance failures may occur. If the number of failures within that window of time
is excessive DUCC will set a disabled flag and no longer restart instances. Instance which do not fail are left
running. The disabled flag must be manually reset once the problem is resolved before new instances can be
started. This default policy may be overridden by custom pingers.

When the last job or service that references the on-demand service exits, a timer is established to keep the
service alive for a while, in anticipation that it will be needed again soon. When the keep-alive timer expires,
and there are no more dependent jobs or services, the reference-started service is automatically stopped to free
up its resources for other work. The time the service is allowed to remain alive is known as its linger time and
can be controlled with the service_linger keyword in the service registration.

Manually started services

A service may be started via the CLI if it is not already running and in the absence
of references by other work. A service which is manually stared by the CLI can only be stopped manually by
the CLI.

As is the case for autostarted and reference-started services, failed instances will be restarted unless the number
of failures within the failure window is exceeded and the disable flag is set.

Ping-Only Services

Ping-only services consist of only a ping thread. The service itself is not managed in any way
by DUCC. This is useful for managing dependencies on services that are not under DUCC control: the pinger
is used to assess the viability of the external service and prevent dependent jobs from continuing if the service
is unavailable.

Only CUSTOM services may be defined as ping-only services in this version of DUCC.

Dynamically Changing Service Policies
A service may be stopped; that is, no instances are running. This state can occur if the service has experienced too many
errors within its failure window, in which case the service is disabled, or because the service is not autostarted or referenced by
other work.

If a manual stop is issued the service will be automatically disabled to insure it cannot be restarted (by reference or at boot
with autostart) without manual intervention.

In all cases, if a service is disabled, it must be manually enabled using the CLI.

It is possible, via the CLI, to dynamically switch any service from any management policy to any other policy, as shown in
the following table.

See the Service CLI reference for details on the various commands described in this section.

Current Mode

Desired Mode

Action

Notes

Autostart

Manual

Use CLI to modify registration to
autstart false.

Service does not stop until requested by
CLI. Service will not start at DUCC
boot.

Autostart

Reference

Use CLI to modify registration to
autostart false and observe references.

Service stops after last reference exits,
plus linger time.

Autostart

Stopped

Use CLI to stop the service.

The CLI stop will by necessity disable
the service to insure it remains stopped.

Reference

Autostart

Use CLI to modify registration to
autostart true.

Service continues to run after last
reference exits. Service always started
at DUCC boot.

Reference

Manual

Use CLI to ignore references.

Service continues to run after last
reference exits.

Reference

Stopped

Use CLI to stop the service.

The CLI stop will by necessity disable
the service to insure it remains stopped.

Manual

Autostart

Use CLI to modify registraiton to
autostart true.

Service will be started on DUCC boots.

Manual

Reference

Use CLI to observe references.

Service will stop after last referencing
job exits, plus linger time..

Manual

Stopped

Use CLI to stop the service.

The CLI stop will by necessity disable
the service to insure it remains stopped.

Stopped

Autostart

Use CLI to modify registration to
autostart true.

Service will start immediately. It may
be necessary to enable the service as
well.

Stopped

Reference

Submit a job or service that references
the service.

It may be necessary to enable the
service as well. The service will stop
after the last referencing work exits,
plus linger.

Stopped

Manual

Use CLI to start the service.

The CLI start will also enable the
service if necessary.

5.7 Service Pingers

A service pinger is a small program that queries a service on behalf of the DUCC Service Manager. A default pinger is
provided for UIMA-AS services and provides the following functions:

Determine if the service is responsive by issuing a UIMA-AS “get-meta” call to the service.

Determine the health of the service by issuing a JMX call to the UIMA-AS broker to collect queueing statistics.

Manage the failure window of the service.

Returns a string with basic ActiveMQ statistics about the service, or error information if the service is deemed
unusable.

Returns date of last use of the service (as determined by presence or absence of service producers attached to
the service queue).

Users may supply their own pingers. The following additional functions are available for pingers. Note that a custom pinger
MAY be supplied for UIMA-AS services, and MUST be supplied for CUSTOM services. Custom pingers use the Service
Manager’s “pinger” API to perform the following tasks:

Inform the Service Manager if the service is viable.

Inform the Service Manager if the service is “healthy”. Service “health” is a heuristic used in the DUCC Web
server as an alert that a service is responding but may not be performing well.

Manage service failure policies. Default failure-window policy is provided to all pingers by the DUCC API
handler (optional).

Return a string describing current service status, for use by the web server.

Instruct the service manager to increase the number of instances (optional).

Instruct the service manager to decrease the number of instances (optional).

Enable and disable the services autostart flag (optional).

Enable logging of a service’s health and state (optional).

Return date of last-use to the Service Manager for display in the webserver (optional).

5.7.1 The Pinger API

Pingers are passed static information about the service at pinger-initialization time, and subsequently, current state of the
service is provided on each call (ping).

Information provided at initialization follows. Most of this is provided in fields in the AServicePing base class. See the
Javadoc for specific field names and types.

Pinger Initialization Data

Data provided once, during pinger initialization, includes:

Arguments

This is the service_ping_arguments string from the service registration.

Endpoint

This is the CUSTOM:string or UIMA-AS:string endpoint provided in the service registration.

Monitor Rate

This is the rate at which the pinger will be called by the SM, as provided in DUCC’s configuration.

Whether the service log is enabled, as specified by the service_ping_dolog registration parameter.

Maximum Allowed Failures

This is the value of the instance_failures_limit parameter, provided by DUCC
configuration and optionally overridden by the service registration.

Instance Failure Window

This is the value of the instance_failures_window parameter, provided by DUCC
configuration and optionally overridden by the service registration.

Autostart Enabled

This indicates whether the service registration currently has the autostart flag enabled.

Last Use

This is the time of last known use of the service, persisted and maintained over SM restarts. It is 0 if
unknown or the service has never been used.

Pinger Dynamic Data

Dynamic information provided to the pinger in each call (ping) consists of:

All Instance Information

This is an array consisting of the unique integer IDS of all running processes
implementing the service. This includes instances which may not be currently viable for some reason (still
initializing, for example).

Active Instance Information

This is an array consisting of the unique integer IDS of all running processes
implementing the service. This is a subset of “All Instance Information” and includes only the service instances
that are advanced to Running state.

Reference Information

This is an array consisting of the unique integer IDS of all DUCC work (Jobs, other
Services, etc) currently referencing the service.

Autostart Enabled

The current state of the service’s autostart flag.

Run Failures

This is the total number of instance failures for the service since the last start of the SM.

Only a Java API is supported.

5.7.2 Declaring a Pinger in A Service

The following registration options are used for declaring and configuring pingers. Any of these may be dynamically modified
with the service CLI’s --modify option. Dynamically changing these causes the current pinger to be terminated and
restarted with the new configuration. See ducc_services for details of the options:

service_ping_arguments

service_ping_class

service_ping_classpath

service_ping_jvmargs

service_ping_timeout

service_ping_dolog

instance_failures_window

instance_failures_limit

5.7.3 Implementing a Pinger

Pingers must implement the class org.apache.uima.ducc.cli.AServicePing. See the Javadoc for the details of this
class.

Below is a sample CUSTOM pinger for a hypothetical service that returns four integers in response to a ping. It illustrates
simple use of the three required methods, init(), stop(), and getStatistics().

5.7.4 Building And Testing Your Pinger

This section provides the information needed to use the pinger API and build a custom pinger.

1. Establish a compilation CLASSPATH
One DUCC jar is required in the CLASSPATH to build your pinger:

DUCC_HOME/lib/uima-ducc-cli.jar

This provides the definition for the AServicePing and ServiceStatistics classes.

2. Create a registration
Next, create a service registration for the pinger. While debugging, it is useful set the directive

service_ping_dolog = true

This will log any output from System.out.println() to the declared log directory for the service. If not specified in the
reqistration, this directory is:

$HOME/ducc/logs/S-<serviceid>/services

where <servicid> is the DUCC-assigned ID of your service.

Once the pinger is debugged you may want to turn logging off.

service_ping_dolog = false

If your pinger requires a different version of Java than is used by DUCC, include a setting for the JAVA_HOME variable in
the environment option.

A sample service registration may look something like the following. Note that you do not need to include any of the
DUCC jars in the classpath for the pinger. DUCC will add the jars it requires to interact with the pinger
automatically. (However you may need other jars to provide UIMA, UIMA-AS, ActiveMQ, Spring, or other
function.)

3. Register and start the service and pinger
Start up your custom service so the pinger with the registration containing lines similar to those above. As soon as the
service instance is in DUCC state Running the SM starts the pinger.

Check the web server to make sure the service “comes alive”. Check your pinger’s debugging log if it doesn’t. Once registered,
you can dynamically modify and restart the pinger at any time without re-registering the service or restarting the service by
use of the --modify option of the ducc_services CLI:

4. If all else fails ...
If your pinger does not work and you cannot determine the reason, be sure you enable service_ping_dolog and look in your log
directory, as most problems with pingers are reflected there. As a last resort, you can inspect the the Service Manager’s log
in

$DUCC_HOME/logs/sm.log

5.7.5 Globally Registered Pingers

A user-built pinger may be registered with DUCC so that it can be globally used by any DUCC service. To do this, a
registration file containing only pinger-specific parameters is created in DUCC’s run-time directory. Such a pinger may then
be designated for a service by using its registered filename instead of its class in the service_ping_class field of a
registration. There is no API or CLI to register such a pinger; only a DUCC administrator may create a global ping
registration.

A globally-registered pinger may then be designated to run as a thread inside the SM or as a process spawned and managed
by the SM. A pinger that runs in a thread in the SM is called an internal pinger, and one that runs in a process is called an
external pinger. An internal pinger generally has nearly unmeasurable impact on the system, whereas external pingers will
occupy full JVMs with processes of 50-100MB or more.

A service may override any of the options of a globally-registered external pinger, thus allowing significant reuse of existing
code. Only the service_ping_arguments of an internal pinger may be overridden however.

The default UIMA-AS pinger is permanently registered as an internal pinger.

Globally registered pingers use a special boolean property, not supported by the ducc_services API/CLI, “internal”, to
determine whether the pinger is to be run internally to SM or as an external process. Only the DUCC administrator may
update a global pinger’s registration to “internal”, to insure such pingers are properly vetted and approved by the
installation.

5.8 Sample Pinger

A sample custom UIMA-AS pinger is provided in the Examples directory shipped with DUCC in

DUCC_HOME/examples/src/org/apache/uima/ducc/ping

This pinger increases or decreases the number of service instances based on the queue statistics found by querying ActiveMQ.
The goal of this pinger is to maintain the ActiveMQ “enqueued time” to be no more than some multiple
of the average service time for a single item. The factor used is a parameter passed in with the argument
string.

5.8.1 Using the Sample Pinger

The following arguments may be specified to use the sample pinger with any UIMA-AS service. The service_ping_arguments
are specific to this pinger.

The following arguments are accepted by this pinger and may be specified in a single single comma-delimited string
containing the following initialization parameters:

meta-timeout

Defines how long to wait for get_meta to return.

broker-jmx-port

Defines the JMX port of the service’s broker.

window

Defines the shrinkage/growth window size, in minutes.

enable-log

Enable extra logging.

min

The minimum number of service instances to maintain.

max

The maximum number of service instances to allow.

max-growth

The maximum number of instances to grow in a single request.

fast-shrink

If set, allow services to shrink if the queue depth is 0, even if consumer are connected. Otherwise we do
not shrink if consumers are attached to the queue.

goal

The multiplier of the ActiveMQ Broker’s average enqeue time to attempt to maintain by managing the number
of instances.

5.8.2 Understanding Sample Pinger

The best way to understand this pinger is to examine the code itself in the Examples directory. Here we provide a brief
line-by-line synopsis of the code.

void init(String args, String ep)
This required method examines the service arguments and endpoint and establishes a monitor to issue get-meta calls to the
service and JMS calls to the ActiveMq broker. The argument string args is described above. The endpoint ep is the service
endpoint used to register the service.

Lines 100-119
These lines parse the endpoint ep its components comprising the UIMA-AS queue name and the URL to the service
broker.

Lines 121-125
These lines disable most UIMA-AS logging as these messages can be quite numerous. However, during debugging it may be
desired to change the logging levels here.

Lines 130-172
These lines parse the service argument string args into its constituent parts and places the values in variables. They initialize
the expansion and deletion window and normalize it to one slot per minute, regardless of the actual ping
rate.

The window normalization uses the DUCC-supplied value monitor_rate to determine the number of slots in the
windows.

Lines 176-177
These lines initialize the DUCC-supplied UimaAsServiceMonitor that queries the UIMA-AS queues, and it resets the queue
statistics via JMX so the monitor can make accurate measurements.

Lines 181-187
These lines implement the required stop method which is invoked when the Service Manager needs to stop the pinger for any
reason. They stop the ActiveMQ queue monitor and emit a shutdown message.

Lines 191-240
These lines define the required getStatistics method. This method collects ActiveMQ statistics, issue get-meta to the service
to see if it is responding, sets the formatted information string into the ping reply, and invokes the code to calculate a
potential redeployment of service instances.

Lines 245-248
These lines override the optional getLastUse method which simply returns the time of last known use of the service. The
actual value is calculated in the pinger-specific calculateNewDeployment method, described below.

Lines 253-298
These lines define the pinger-specific calculateNewDeployment method. This is invoked after get-meta is called and after the
UIMA-AS queue has been queried in ActiveMQ. This is the key method of this pinger. It uses information passed in on the
last ping from the Service Manager in conjunction with information in the ActiveMQ queue to determine if more, or fewer
service instances are needed to meet the performance goals. If fewer instances are needed, it selects specific instances to stop.
The method is described in detail below.

Lines 407-410
These lines override the optional getAdditions method. The method returns the number of new service instances required to
meet performance goals, as calculated in calculateNewDeployment.

Regardless of what this method returns, the Service Manager may choose not to start new instances, based on its configured
maximum, ducc.sm.max.instances as defined in ducc.properties.

Lines 416-419
These lines override the optional getDeletions method. This method returns the specific service instances to be stopped, if
any.

The DUCC-assigned unique IDs of all service instances are passed in to the pinger on each ping. These instances are
monotonically increasing over time so pingers may assume that lower numbers represent older instances.

Lines 429-480
These lines define a class used as a call-back on the UIMA-AS get-meta requests to determine the host and PID of the service
instance responding to the get-meta. If the get-meta request should timeout, this information can be used to help identify
ailing or overloaded service instances.

5.8.3 Calculating New Deployments in the Pinger

his section details the use of ActiveMQ queue statistics in conjunction with the Service Monitor data to calculate the number
of service instances to increase or decrease.

It is important that this code be very careful about “smoothing” the performance statistics to keep growth and shrinkage
stable. Things to take into consideration include:

1.

Immediately after a new service instance becomes available to serve, if there is demand for this service, the
ActiveMQ statistics will fluctuate for a few minutes until traffic stabilizes. Thus decisions based on these
statistics must reflect history as well as current information.

2.

Immediately after a client begins to use a service, the statistics will also fluctuate, again requiring smoothing.

3.

The DUCC work dispatching model will not over-dispatch work to the job processes. Thus actual demand on a
service is a function of the number of actively deployed and initialized JPs. If the number of JPs decreases due
to preemption, demand on the service by that job will decrease proportionally. Similarly, demand can increase
as the job expands.

It is common for demand on a service to ramp up slowly as a job enters the system, and increase rapidly as a
job completes its initialization phase and starts to double. Thus, the ActiveMQ statistics can be quite erratic
for a while, until the job stabilizes.

This again requires some sort of smoothing of the data when making decisions about service growth and
shrinkage.

To handle this data smoothing, the SamplePing classes uses two time-based windows, one for growth, and one for shrinkage,
to keep growth and shrinkage stable. The window size is defined in the service ping argument window. Each window period, if
more services are needed, a mark is made in the current slot of the expansion window; otherwise the current slot is cleared.
Similarly, each period, if fewer services are needed, a mark is made in the shrinkage window; otherwise, the current slot is
cleared.

After the marks are made, if the expansion window has all slots filled, a request for new processes is made;
thus, a short period of increased does not destabilize the system with a request for services that may be of
little use. Additionally, when a request is made, the number of new processes requested is capped by the
ping argument max-growth to insure that the service grows smoothly. And finally, if the service is already at
some configured maximum number of instances, defined by the max parameter, no additional instances are
requested.

Similarly, the shrinkage window is used to govern shrinkage. All slots must be filled, indicating the service has been
over-provisioned for a while, before a request is made to delete instances. The number of instances is never
reduced below the configured min value. As well, this particular pinger never shrinks by more than a single
instance at a time, on the reasoning that it is more costly to start a new service than to maintain one for
too long. Only if there is no long-term use of the extra instances are they reduced (as determined by the
window).

Given this introduction, we describe the key method in detail.

Lines 262-277
These lines extract four quantities from the ActiveMQ statistics:

1.

Average enqueue time, eT

2.

Current queue depth, Q

3.

The current number of service consumers cc

4.

The current number of service producers pc

The code then gets the DUCC IDs of all the currently started service instances, and the number of instances that are started
but still in their “initialization” phase. This is important because instances that are still initializing are not servicing the
queue, but will soon start to do so. The current ActiveMQ statistics reflect do NOT yet reflect this however, they reflect only
the instances that are actually serving.

Finally, if there are service producers, we note the time of day to return to the SM as the last known use of this service by
some process.

Lines 267
This line calculates the number of Java threads per service instance, needed to calculate the maximum capacity of the service
in its current deployment.

(Note that in each UIMA-AS service, UIMA-AS itself occupies one thread, used to manage the service, and this thread
manifests itself as a consumer on the queue.)

Line 301
This declares new_ni, the number of additional instances, if any. At the end of this method, new_ni will either be 0 or
>0.

Lines 303-312
If the current queue depth is 0 (Q == 0), we know a number of things:

1.

The service is not over-provisioned; there is no work queued and waiting for some service. We therefor do not
need to expand.

2.

If there are no consumers, i.e. no clients that need work done, we are potentially over-provisioned, so we fill in
a slot in the expansion window.

If there are consumers, we may not want to shrink because it is possible that one of the service instances is
busy; we cannot tell. So we allow the fast-shrink ping argument to govern whether or not connected consumers
may prevent service shrinkage.

There is nothing else that can be said about a service if its current queue depth is 0.

Lines 312-360
If the queue depth is non-zero we are able to calculate the total service capacity and the amount each instance contributes to
the total capacity. From this we can determine

1.

whether the service is performing at or near its goal,

2.

if the service is performing worse than its goal, how many new instances are needed to meet the goal, and

3.

if the service is performing better than its goal, how many instances can be given up and still meet the goal.

Details follow.

Lines 314 and 315
The average time a single instance takes to serve a single request, Ti is given by the simple formula

Ti = (eT / Q) * active

where

eT

is the average time an item stays in queue (from AMQ),

Q

is the current queue depth (from AMQ),

active

is the current number of service instances (from SM)

Therefore the time taken by a single thread Ti is given by

Tt = Ti * nthreads

Lines 319 and 320
We want Tt to become close to the current

Tt * goal

where goal is given by the ping arguments. The current ratio of actual service time to desired is then given
by

r = eT / g

Because we know that the DUCC job driver will never over-commit; that is, we know the current demand will remain
constant unless the jobs using the service expand or contract (which are relatively rare events), we can state that the number
of service instances required is directly proportional to r.

If r > 1 we may need more instances to meet our goal and if r < 1 we may be over-provisioned.

Lines 325-347
If r > 1 we may be over-provisioned. We calculate the number of required instances by multiplying the current instances by r
and rounding down. We account for instances that we know are starting but not yet started, cap on max instances per
service, and again on max growth per cycle.

If we still require additions, we make a mark in the expansion window, otherwise we clear the expansion window.

Lines 349-360
If r < 1 we need to calculate shrinkage. Because starting instances is expensive we conservatively use r < .5 instead and make
a mark in the shrinkage window.

Otherwise we clear the mark in the shrinkage window.

Lines 367-396
Finally we sum across the shrinkage and expansion windows. If either window is full, we schedule growth (line 375, set the
variable additions) or shrinkage (line 388, set deletions).

Note that to schedule shrinkage, we must choose a specific instance. In this case we choose the newest instance, i.e. the one
with the largest DUCC ID, as it is most likely not to have initialized, or perhaps not to have “warmed up” (i.e. caches filled,
etc.). We could choose more than one but this pinger is conservative and only shrinks by one instance each
time.

5.8.4 Summary of Sample Pinger

This pinger illustrates these functions over-and above the functions provided by the default UIMA-AS pinger:

1.

Use of pinger-specific arguments

2.

Use of information provided by SM on each ping (service instances active, total service instances,

3.

Use of performance information acquired from ActiveMQ

4.

Requesting new service instances of the SM

5.

Requesting that instances be removed by SM,

6.

Setting of last-use of a service

It illustrates one mechanism for smoothing growth and shrinkage of a service to prevent thrashing in your
system.

It illustrates one mechanism for determining the actual performance of a service by analyzing ActiveMQ queueing
statistics.

It illustrates the use of “globally registered pingers.”

Chapter 6Job Logs

The ”user logs” are the Job Driver (JD) and Job Process (JP) logs. There is one JP log for each process of a job. These hold
the redirected stdout and stderr messages from user code as well as some DUCC-generated messages. These DUCC messages
are managed by Apache log4j using the configuration file $DUCC_HOME/resources/log4j.xml. It is not in the
scope of this document to describe log4j or its configuration mechanism. Details on log4j can be found at
http://logging.apache.org/log4j.

Contents of the Log Directory
A number of other useful files are written to the log directory:

1.

A properties file containing the full job specification for the job. This includes all the parameters specified by
the user as well as the default parameters. This file is called job-specification.properties.

2.

The UIMA pipeline descriptor constructed by DUCC that describes the process that is dispatched to each Job Process
(JP). The name of this file is of the form

JOBID-uima-ae-descriptor-PROCESS.xml

where

JOBID

This is the numerical id of the job as assigned by DUCC.

PROCESS

This is the process id of the Job Driver (JD) process.

3.

The UIMA-AS service descriptor that defines the process that defines the job as as UIMAAS service. The name of this
file is of the form

JOBID-uima-as-dd-PROCESS.xml

where

JOBID

This is the numerical id of the job as assigned by DUCC.

PROCESS

This is the process id of the Job Driver (JD) process.

4.

A colllection of gzipped “json” files containing the performance breakdown of the job.

Job Process Logs
The Job Process logs are written to the configured log directory. There is one job process log for every job processes started
for the job. The log names are of the following form:

returns isKillJob == false, unless the number of work items errors exceeds 15 for the Job

2.

returns isKillProcess == true

3.

returns isKillWorkItem == true

Programmability
The Job Driver built-in (or custom) ErrorHandler behavior can be modified according to the driver_exception_handler_arguments
string in the Job Specification. Currently recognized are:

max_job_errors=E

, where E is the maximum number of work item errors tolerated before terminating the Job.
Default is 15.

max_timeout_retrys_per_workitem=R

, where R is the maximum number of work item timeouts tolerated
before the work item is considered an error. Default is 0.

Replacement
The ErrorHandler can be replaced. The steps necessary are:

1.

Create a new org.myOrg.myProject.MyErrorHandler.class that implements
org.apache.uima.ducc.IErrorHandler, which is located in the uima-ducc-user.jar.

2.

Put your replacement class in your Job Specification classpath.

3.

Put your replacement class name as the value for your Job Specification driver_exception_handler.

Chapter 8DUCC Web Server

The DUCC Web Server default address is accessed from the URL http://[DUCC-HOST]:42133. The [DUCC-HOST] is the
hostname where the local installation has installed the DUCC Web Server.

The hostname and port are configurable by the DUCC administrator in ducc.properties

The Webserver is designed to be mostly self-documenting. The design is intentionally simple and contains a link to this
document. Most of the interesting fields and column headers have “mouse hovers” which display a short description if you
hover your mouse pointer over it for a moment.

Figure 8.1: Sample Webserver Page

Normally, the Web Server automatically fetches new data from DUCC and updates the display. This is controlled by setting
one of the two refresh modes:

Manual refresh. In this mode, the browser windows are updated only by using the browser’s refresh button, or
the DUCC refresh button to the left in the header of each page.

Automatic refresh. In this mode, the browser automatically fetches and displays new data. The rate of refresh
is currently fixed and cannot be configured.

There is a behavior difference between refresh and reload.

Refresh
Refresh causes the current data on the page to be updated with the most current information in the Webserver’s possession.
This is performed when the refresh button is clicked.

Reload
Reload occurs when the enter key is pressed. Reload causes not just the data to be updated but rather the entire page is
replaced.

Two different table styles are supported:

Scroll, and

Classic.

Table styles are switched using the Preferences link.

Scroll Mode
When scroll table style is the preference, a scroll bar is shown to the right, within the main window. The scroll bar allows
scrolling to be restricted to the data display, leaving column and DUCC headers in place. In this mode any column may be
sorted simply by clicking on it.

With respect to sorting, any specified sort is remembered for refresh but forgotten for reload. Sorting is permitted when
either manual or automatic refresh mode is selected.

The column sort order is maintained until the page is reloaded.

Note that not all pages have a scroll version - some only have a classic version.

Classic Mode
When classic table style is the preference, the main data may extend below the bottom of the page and it will be necessary to
use the browser’s scroller on the right to access it. The column headers and DUCC header scrolls off when doing this.
Columns may be sorted in this mode but it is necessary to first switch to “Manual” refresh mode to prevent browser refreshes
during sorting and display of data.

With respect to sorting, any specified sort is forgotten for refresh and reload. Sorting is only permitted when manual refresh
mode is selected.

The column sort order is maintained until the page is refreshed or reloaded.

Figure 8.2: Preferences Page

8.1 Common Links

Every page contains a common header containing links and controls. The links permit navigation to other content at the site.
The controls provide page-wise configuration of the content at that page.

The following links are available on every page of the web server:

Authentication

Authentication is needed in order to cancel jobs and reservations, to create a reservation, and to perform
administration. It is not required to simply view the pages.

Login - Authenticate and start a session with the Web Server.

Logout - Terminate the Web Server session

Preferences

The following preferences may be set:

Table Style

This selects “scroll” or “classic” display, as described above.

Date Style

This selects long, medium, or short formats for dates.

Description Style

This selects long or short formats for the various description fields.

Display Style

Choose to display text or (in some circumstances) icons.

Filter Users

This controls the “filter” box near the middle of the header on each page. It allows various levels
of inclusion and exclusion of active or completed work for the filtered users.

Role

This allows selection of “User” or “Administrator” roles. This protects registered DUCC administrators
from accidentally affecting other people’s work.

DuccBook

This is a link to the HTML version of the document you are reading.

Jobs

This navigates to the Jobs page, showing all the jobs in the system.

Reservations

This navigates to the Reservations page, showing all the reservations in the system and provides a button that can be
used to request new reservations.

Services

This navigates to the Services page, showing all the services in the system.

System

This opens a sub-menu with system-related links:

Administration - This opens a page with administrative functions.

Broker - This shows information about the AMQ broker employed by the system.

Classes - This shows all the scheduling classes defined to the system.

Daemons - This shows the status of DUCC’s management processes.

DuccBook - This manual.

Machines - This shows the status of all the DUCC worker nodes.

Viz

This opens a page with a visualization of the system hosts, showing all scheduled work in the system.

8.2 Login

Access for monitor and update capability via the Web Server is controlled by login. Logs, files and other data are accessed by
the Linux permissions of the logged-in user.

Specifications for Jobs and Managed Reservations are kept in the database. Read access is granted for a logged-in user via
site-security-directory/.ducc/db.access file read permission.

For the Services Registry in particular, the following attributes give the Web Server browsing user read or write
access:

8.3 Jobs Page

The Web Server’s home page is also the Jobs page. This page has links to all the rest of the content at the site and shows the
status of all the jobs in the system.

The Jobs page contains the following columns:

Id

This is the ID as assigned by DUCC. This field is hyperlinked to a Job Details page for that job that shows
the breakdown of all the processes assigned to the job and their state.

Start

This is the time the Job is accepted into DUCC.

Duration

This shows two times. In green the length of time the job has been running. In red is the estimated time of
completion, based on current resources and remaining work. When the job completes, the time shown is the
total elapsed time of the job.

User

This is the userid of the job owner.

Class

This is the resource class the job is submitted to.

State

This shows the state of the job. The normal job progression is shown below, with an explanation of what each state
means.

Received

- The job has been vetted, persisted, and assigned a unique ID.

WaitingForDriver

- The job is waiting for the Job Driver to initialize.

WaitingForServices

- The job is waiting for verification from the Service Manager that required services are
started and responding. This may cause DUCC to start services if necessary. In that event this state will
persist until all pre-requisite services are ready.

WaitingForResources

- The job is waiting to be scheduled. In busy systems this may require preemption of
existing work. In that case this state will persist until preemption is complete.

Initializing

- The job initializing. Usually this is the UIMA-AS initialization phase. In the default
configuration, only two (2) processes are allocated by the Resource Manager. No additional resources are
allocated until at least one of the new processes successfully completes initialization. Once initialization is
complete the Resource Manager will double the number of allocated processes until the user’s fair share
of the resources is attained.

Running

- At least one process is now initialized and running.

Completing

- The last work item has completed and DUCC is freeing resources. If the job had many resources
allocated at the time the job exited this state will persist until all allocated resources are freed.

Completed

- The job is complete.

Reason or Extraordinary Status

This field contains miscellaneous information pertaining to the job. If the job exits the system for any reason, that
reason is shown here. If the job’s pre-requisite services are unavailable (or ailing) that fact is displayed here. If there is a
job monitor running, that fact is shown here. Most of the values for this field support “hovers” containing additional
information about the reason.

EndOfJob

- The job and completed ran with no errors.

Error

- All work items are processes but at least one had an error.

CanceledByDriver

- The Job Driver (JD) terminated the job. The reason for termination is seen by hovering
over the text with your mouse.

CanceledBySystem

- The job was canceled because DUCC was shutdown.

CanceledByUser

- The job owner or DUCC administrator canceled the job.

Cancel Pending

- The job has been canceled and is not yet fully evicted from the system.

DriverInitializationFailure

- The Job Driver (JD) process is unable to initialize. Hover over the field with
your mouse for details (if any are available), and check your JD log.

DriverProcessFailed

- The Job Driver (JD) process failed for some reason. Hover over the field with your
mouse for details (if any), and check your JD log.

MonitorActive

The job has a console monitor active. This is enabled with the job’s “wait_for_completion”
parameter on job submission.

ServicesUnavailable

- The job declared a dependency on one or more services, and the Service Manager
(SM) cannot find or start the required service.

Premature

- The job was terminated for some unknown reason before all work items were processed. Check
the JP logs for details.

ProcessInitializationFailure

- Too many processes failed during initialization and the job was canceled by
DUCC. Check the JP logs for the reason.

ProcessFailure

- Too many processes failed while running and DUCC canceled the job. Check the JP logs
for the reason.

ResourcesUnavailable

- The Resource Manager (RM) is unable to allocate resources for the job. For
non-preemptable jobs this could be because the limit on that type of allocation is reached, or all the hosts
are already allocated and work cannot be preempted to make space for it. For all jobs, it could be because
the job class is invalid.

service_name

If there is a service name in this field it indicates the job is dependent on the service but the
service is not responding to the DUCC Service Monitor’s pinger.

Services

This is the number of services the job has declared dependencies on. There is a “hover” that shows the ids of the
services, if any.

Processes

This is the number of processes currently assigned to the job.

Init Fails

This is the total number of initialization failures experienced by the job. This field is hyperlinked to pages with log
excerpts highlighting the specific failures.

Run Fails

This is the total number of process failures experienced by the job. This field is hyperlinked to pages with log excerpts
highlighting the specific failures.

PgIn

This is the number of page-in events, over all processes, on the machines running the job.

Swap

This is the total swap space, over all the processes, being used by the job.

Memory

This is the declared memory size of the job

Total

This is the total number of work items declared by the job.

Done

This is the total number of work items successfully completed for the job.

Error

This is the total number of exceptions thrown or other errors experienced by work items. This field is hyperlinked to
pages containing log excerpts highlighting the failures.

Dispatch

This is the total number CASs that are currently dispatched.

This usually represents the quantity derived from the following formula:

The actual number is a measured number, not a calculated number, and may differ slightly from the formula if the
measurement is taken immediately after process start-up, or in the time between a work item completing and a new one
being dispatched.

Retry

This is the number of CASs that were retried for any reason. Reasons for retry include preemption for fair-share,
work-item timeout, or error conditions.

Note: If a work item in any process fails, the entire process is considered suspect, and all work-items in the process are
terminated. Work items in the process which did not have errors are re-dispatched (retried) to a different
process.

Preempt

This is the total number of work-items that have been preempted to make room for other work due to Fair
Share.

Description

This is the description string from the --description string from submit.

Figure 8.3: Jobs Page

8.4 Job Details Page

This page shows details of all the processes that run in support of a job. The information is divided among five
tabs:

Processes

This tab contains details on all the processes for the job, both active, and defunct.

Work Items

This tab shows details for each individual work-item in the job.

Performance

This tab shows a performance break-down of all the UIMA analytics in the job.

Specification

This tab shows the job specification for the job.

Files

This tab shows the files in the log directory.

8.4.1 Processes

The processes page contains the following columns:

Id

This is the DUCC-assigned numeric id of the process (not the Operating System’s process Id). Process 0 is
always the Job Driver.

Log

This is the log name for the process. It is hyperlinked to the log itself.

Log Size

This is the size of the log in MB. If you find you have trouble viewing the log from the Web Server it could be
because it is too big to view in the server and needs to be read by some other means than the Web Server. (It
is not currently paged in by the Web Server, it is read in full.)

Host Name

This is the name of the host where the process ran.

PID

This is the Unix process ID (PID) of the process.

State Scheduler

This shows the Resource Manager state of the job. It is one of:

Allocated

- The host is currently allocated for this job by the RM.

Deallocated

- The resource manager has deallocated the shares for the job on this host.

Reason Scheduler or extraordinary status

This column provides a reason for the scheduler state, when the scheduler state is other than “Allocated”. These may
have “hovers” that provide more information if it is available.

AutonomousStop

- The process terminated unexpectedly of its own accord (”crashed”, or simply exited.)

Exception

- The process is terminated by the JD exception handler.

Failed

- The process is terminated by the Agent because the JP wrapper was able to detect and communicate
a fatal condition (Exception) in the pipeline..

FailedInitialization

- The process is terminated because the UIMA initialization step failed.

Forced

- The host is preempted by RM for other work because of fair share.

JobCanceled

- The job was canceled by the user or a system administrator.

JobCompleted

- The process is canceled because of DUCC restart.

JobFailure

- The job failure limit is exceeded, causing the job to be canceled by the JD.

InitializationTimeout

- The UIMA initialization phase exceeded the configured timeout.

Killed

- The agent terminated the process for some reason. The “Reason Agent” field should have more details
in this case.

Stopped

- The process was terminated by the Agent for some reason. The hover should contain more
information.

Voluntary

- The job is winding down, there’s no more work for this host, so it stops.

Unknown

- None of the above. This is an exceptional condition, sometimes an internal DUCC error. Check
the JP and JD logs for possible causes..

State Agent

This shows the DUCC Agent’s view of the state of the process.

Starting

The DUCC process manager has issued a request to the assigned DUCC Agent to start the process.

Started

The assigned DUCC Agent has started the process.

Initializing

The process is initializing. Usually this means the UIMA analytic pipeline (Job Process) is
executing its initialization method.

Running

The Job Process has completed the initialization phase and is ready for or actively executing work.

Stopped

The DUCC Agent reports the process is stopped and (and has exited).

Failed

The DUCC Agent reports the process failed with errors. This usually means that UIMA-AS has detected
exceptions in the pipeline and reported them to the Job Driver for logging.

FailedInitialization

The process died during the UIMA initialization phase.

InitializationTimeout

The process exceeded the site’s limit for time spent in UIMA initialization.

Killed

The DUCC Agent killed the process for some reason. There are three reasons for this:

1.

The Job Processes failed to initialize,

2.

The Job Process timed out during initialization,

3.

The process exceeded its allowed swap.

Abandoned

It is possible to cancel a specific process of a job. Usually this is because it became “stuck” because of
hardware failure. If a process is killed in this way, the state is recorded as Abandoned.

Reason Agent

This shows extended reason information if a process exited other than having run out of work to do.

AgentTimedOutWatingForORState

The DUCC Agent is expecting a state update from the DUCC
Orchestrator. Timer on this wait has expired. This usually indicates an infrastructure or communication
problem.

Croaked

The process exited for no good or clear reason, it simply vanished.

Discontinued

This is the normal reason when the process is stopped as directed.

ExceededShareSize

The process exceeded it’s declared memory size.

ExceededSwapThreshold

The process exceeded the configured swap threshold.

FailedInitialization

The process was terminated because the UIMA initialization step failed.

InitializationTimeout

The process was terminated because the UIMA initialization step took too long.

JPHasNoActiveJob

This is set when an agent looses connectivity while its JPs are running. The job finishes
(stopped or killed). The agent regains connectivity. The OR publish no longer includes the job but the agent
still has processes running for that job. The agent kills ghost processes with the reason: JPHasNoActiveJob.

LowSwapSpace

The process was terminated because the system is about to run out of swap space. This is
a preemptive measure taken by DUCC to avoid exhaustion of swap, to effect orderly eviction of the job
before the operating system starts its own reaping procedures.

AdministratorInitiated

The process was canceled by an administrator.

UserInitated

The process was canceled by the owning user.

Exit

The process exit code or signal.

Time Init

This is the clock time this process spent in initialization.

Time Run

This is the clock time this process spent in executing, not including initialization.

Time GC

This is amount of time spent in Java Garbage Collection for the process.

PgIn

This is the number of page-in events on behalf of the process.

Swap

This is the amount of swap space on the machine being consumed by the process.

%CPU

Current CPU percent consumed by the process. This will be > 100% on multi-core systems if more than one core is
being used. Each core contributes up to 100% CPU, so, for example, on a 16-core machine, this can be as high as
1600%.

RSS

The amount of real memory being consumed by the process (Resident Storage Size)

Time Avg

This is the average time in seconds spent per work item in the process.

Time Max

This is the maximum time in seconds spent per work item in the process.

Time Min

This is the minimum time in seconds spent per work item in the process.

Done

This is the number of work items processed in this process.

Error

This is the number of exceptions processing work items in this process.

Dispatch

The number of work items currently dispatched.

Retry

This is the number of work items that were retried in this process for any reason, excluding preemption.

Preempt

This is the number of work items that were preempted from this process, if fair-share caused preemption.

JConsole URL

This is a URL that can be used to connect via JMX to the processes, e.g. via jconsole.

Figure 8.4: Processes Tab

8.4.2 Work Items

This tab provides details for each individual work item. Columns include:

SeqNo

This is the sequence work items are fetched from the Collection Reader’s getNext() method by the DUCC Job
Driver.

Id

This is the name of the work item.

Status

The is the current state of the work item. States include:

ended

The work item is complete.

error

The work item ended with errors.

operating

The work item is current being executed.

retry

The work item is being retried.

start

The work item has been picked up for execution and DUCC is waiting for confirmation that it is running.

If a work item has not yet been retrieved from the Collect Reader it does not show on this page.

Delivery Time (sec)

The time spent in getting a work item from the Job Driver to a Job Process.

Process Time (sec)

The time spent processing the work item.

Investment Time (sec)

The time spent processing the work item during the current epoch.

Node (IP)

The host IP where the work item was processed.

Node (Name)

The host name where the work item was processed.

PID

The Unix Process Id that the work item was processed in.

Figure 8.5: Work Items Tab

8.4.3 Performance

This tab shows performance summaries of all the pipeline components. The statistics are aggregated over all instances of each
component in each process of the job.

Name

The short name of the analytic.

Total

This is the total time in days, hours, minutes, and seconds taken by each component of the pipeline.

% of Total

This is the percent of the total usage consumed by this analytic.

Avg

This is the average time spent by all the instances of the analytic.

Min

This is the minimum time spent by any instance of the analytic.

Max

This is the maximum time spent by any instance of the analytic.

Figure 8.6: Performance Tab

8.4.4 Specification

This tab shows the full job specification in the form of a Java Properties file. This will include all the parameters specified by
the user, plus those filled in by DUCC.

Figure 8.7: Specification Tab

8.4.5 Files

This tab shows the files in the log directory.

8.5 Reservations Page

This page shows details of all reservations. There are two types of reservations: managed and unmanaged.

A managed reservation is a reservation whose process is fully managed by DUCC. This process is any arbitrary process and is
submitted with the ducc_process_submit CLI. The lifetime of the reservation starts at the time DUCC assigns a unique ID,
and ends when the process terminates for any reason.

An unmanaged reservation is essentially a sandbox for the user. DUCC starts no processes in the reservation and manages
none of the processes which run on that host. The lifetime of the reservation starts at the time DUCC assigns a unique ID,
and ends when the submitter or system administrator cancels it.

The Reservations page contains the following columns:

Id

This is the unique DUCC numeric id of the reservation as assigned when the reservation is made. If this is a
managed reservation, the ID is hyperlinked to a Managed Reservation Details page with extended details on
the process running in the reservation.

Start

This is the time the reservation was made.

Duration

A time in green is the length of time the active reservation has been assigned. A time in black is the length of
time the completed reservation was assigned.

User

This is the userid that made the reservation.

Class

This is the scheduling class used to schedule the reservation.

Type

This is the reservation type, managed or unmanaged, as described above.

State

This is the status of the reservation. Values include: Received - Reservation has been vetted, persisted, and assigned
unique Id.

Assigned

- The reservation is active.

Completed

- The reservation has been terminated.

Received

- The Reservation has been vetted, persisted, and assigned a unique ID.

WaitingForResources

- The reservation is waiting for the Resource Manager to find and schedule resources.

Reason

If a reservation is not active, this shows the reason. Note that for unmanaged reservations, even if the user has
processes running in the reservation, DUCC does NOT attempt to terminate those processes (hence,
“unmanaged”.)

For managed reservations, DUCC does terminate the associated process.

CanceledBySystem

- In the case of the special JobDriver reservation, this is canceled by DUCC and
reestablished on reboot; hence the state is a result of DUCC having been restarted.

In all other cases, it is a result of DUCC being restarted COLD. When DUCC is started COLD, all
previous reservations are canceled. (When DUCC is started WARM, the default, previous reservations are
preserved.)

CanceledByAdmin

- The DUCC administrator released the reservation.

CanceledByUser

- The reservation owner released the reservation.

ResourcesUnavailable

- The Resource Manager was unable to find free or freeable resources to match the
resource request.

ProgramExit

- The reservation is a managed reservation and the associated process has exited.

User Processes

This is the number of processes owned by the user running in the reservation.

Note that even for unmanaged reservations, the DUCC agent tracks processes owned by the user and reports on them.
This allows better identification and management of abandoned reservations.

PgIn

This is the number of page-in events for the managed reservation.

Swap

This is the total swap space for the managed reservation.

Memory

The memory size in GB of the reservation. This is the amount of memory that was requested. In the case of RESERVE
policy reservations, that actual memory of the reserved machine may be greater.

Host Names

The host names of the machines where the resources are allocated.

Description

This is the description string from the –description string from submit.

Figure 8.8: Reservations Page

8.6 Managed Reservation Details Page

This page shows details of the processes which run in a managed reservation. The information is divided between three
tabs:

Processes

This tab contains details on all the processes contained in the reserved space.

Specification

This tab shows the specification for the process.

Files

This tab shows the files in the log directory.

8.6.1 Processes

The processes page contains the following columns:

Id

This is the DUCC-assigned numeric id of the process. This format of this id is two numbers:

RESID.SHAREID

Here, the RESID is the reservation ID. The SHAREID is the share ID assigned by the Resource Manager. Together
these form a unique ID for each process that runs in the reservation.

Note: The current version of DUCC supports only one process per managed reservation. Future versions are expected to
support multiple processes within a single managed reservation.

Log

This is the log name for the process. It is hyperlinked to the log itself.

Log Size

This is the size of the log in MB. If you find you have trouble viewing the log from the web server it could be because it
is too big to view in the browser.

Host Name

This is the name of the host where the process is running (or ran).

PID

This is the Unix process ID (PID) of the process.

State Scheduler

This shows the Resource Manager state of the job. It is one of:

Allocated

- The resource manager has allocated resources for this process on the host.

Deallocated

- The resource manager has deallocated resources for this process on the host.

The current duration of the reservation, or total duration if it has terminated.

PgIn

This is the number of page-in events on behalf of the process.

Swap

This is the amount of swap space on the machine being consumed by the process.

%CPU

Current CPU percent consumed by the process. This will be > 100% on multi-core systems if more than one core is
being used. Each core contributes up to 100% CPU, so, for example, on a 16-core machine, this can be as high as
1600%.

RSS

The amount of real memory being consumed by the process (Resident Storage Size)

8.6.2 Specification

This tab shows the full managed reservation specification in the form of a Java Properties file. This will include all the
parameters specified by the user, plus those filled in by DUCC.

8.6.3 Files

This tab shows the files in the log directory.

8.7 Services Page

This page shows details of all services.

The Services page contains the following columns:

Id

This is the unique numeric DUCC id of the service. This ID is hyperlinked to a Service Details page with
extended details on the service. Note that for some types of services, DUCC may not know more about the
service than is shown on the main page.

Name

This is the unique service endpoint of the service.

State

This is the state of the service with respect to the service manager. It is a consolidated state over all the service
instances. Valid states are

Available

At least one service instance is responding to the service pinger, indicating it is functional.

Initializing

No service instances are available for use yet but at least one instance is in its UIMA initializing
phase.

Waiting

At least one service instance is in Running state, potentially available for use, but no response has
been received from the service pinger. This usually occurs during the start-up of a service. If a service
stops responding to its pinger after becoming available, the state can regress to Waiting.

NotAvailable

No service instance is running or initializing.

Stopped

The service has been stopped.

Stopping

The service has been stopped for some reason, but not all instances have terminated. This is an
intermediate state between Available and NotAvailable to signify that the service is no longer available
but not all its resources have been returned yet.

DUCC will start dependent jobs ONLY if its services are in state Available. Otherwise DUCC attempts to start the
service, and if successful, allows the job to start.

If a job is already running and a service becomes other than Available, the jobs page indicates the service is not
available but the job is allowed to continue.

Last Use

The time this service was last used.

Instances

This is the number of instances (processes) currently registered for the service.

Deployments

This is the number of actual instances deployed for the service. Note that this may be greater, or less, than
the number of registered instances, if the service owner decides to temporarily start or stop additional
instances.

Start State

This service start state.

User

This is the userid of the service owner.

Class

This is the scheduling class the service is running in.

If a service is registered as “ping-only”, no resources are allocated for it. This is shown as a class of
ping-only.

PgIn

This is the number of page-in events on behalf of the service.

Swap

This is the amount of swap space consumed by the service.

Memory (registered)

This is the memory size, in GB, of each service instance

Jobs

This is the number of jobs currently using the service. The IDs of the jobs are shown as hovers over this
field.

Services

Services may themselves depend on other services. This field shows the number of services dependent on this service.
The dependent service IDs are shown with a hover over the field.

Reservations

This field shows the number of managed reservations dependent on this service. The IDs of the managed reservations
are shown as a hover over the field.

Description

This is the description string from the –description string from submit.

8.8 Service Details Page

This page shows details of the processes which implement.

The information is divided between four tabs:

Deployments

This tab contains details on all the processes implementing the service, if any.

Registry

This tab shows the registration information for the service.

Files

This tab shows the files in the log directory.

History

This tab contains details on all the completed processes implementing the service, if any.

8.8.1 Deployments

The deployments page contains the following columns:

Id

This is the DUCC-assigned numeric id of the process. This format of this id is two numbers:

RESID.SHAREID

Here, the RESID is the Orchestrator assigned instance ID. The SHAREID is the instance ID assigned by the Resource
Manager. Together these form a unique ID for each process that runs in the service.

State

The state of this service instance.

Services

The current state of service dependencies.

Log

This is the log name for the process. It is hyperlinked to the log itself.

Log Size

This is the size of the log in MB. If you find you have trouble viewing the log from the web server it could be because it
is too big to view in the browser.

Host Name

This is the name of the node where the process is running (or ran).

PID

This is the Unix process ID (PID) of the process.

Memory

The service process actual memory size (GB).

State Scheduler

This shows the Resource Manager state of the service instance. It is one of:

Allocated

- The node is still allocated for this service instance by the RM.

Deallocated

- The resource manager has deallocated the resources for the service instance on this node.

Most services are UIMA-AS services and therefore have an initialization phase to their lifetimes. This field shows the
time spent in that phase.

Time Run

The current duration of the instance, or total duration if it has terminated.

Time GC

This is amount of time spent in Java Garbage Collection for the process.

Pgin

This is the number of page-in events on behalf of the process.

Swap

This is the amount of swap space on the machine being consumed by the process.

%CPU

Current CPU percent consumed by the process. This will be > 100% on multi-core systems if more than one core is
being used. Each core contributes up to 100% CPU, so, for example, on a 16-core machine, this can be as high as
1600%.

RSS

The amount of real memory being consumed by the process (Resident Storage Size)

JConsole URL

This is a URL that can be used to connect via JMX to the processes, e.g. via jconsole.

8.8.2 Registry

This tab shows the full service specification in the form of a Java Properties file. This will include all the parameters specified
by the user, plus those filled in by DUCC.

The registry for a Service contains two types of entries:

1.

Service specification properties, prefixed with “svc”. These comprise the service specification that the Service
Manager submits on behalf of a user in order to start registered services.

2.

Meta properties, prefixed with “meta”. This is the Service Manager’s state record for the service as it is
running. In addition to state it contains properties required for service registration that are not used for service
submission.

8.8.3 Files

This tab shows the files in the log directory.

8.8.4 History

This tab shows the completed service instances.

8.9 System Pages

These pages show information relating to the DUCC System itself:

Administration

This displays system administrators and implements the interface to various administrative
controls.

Broker

This shows selective information for the system’s broker.

Classes

This shows the system’s scheduling class definitions.

Daemons

This shows the status of all DUCC processes.

DuccBook

This is a link to the book you are reading.

Machines

This shows details of all the machines (nodes) in the DUCC cluster.

8.9.1 Administration

This page has two tabs:

Administrators

This shows the user-ids that are authorized to administer DUCC. In addition to executing the
“Control” functions described below, administrators may cancel any job, reservation, or service, and may modify
services they do not own.

In order to perform administrative functions, the following must be satisfied:

1.

The user is logged-in to the web server.

2.

The user is a registered administrator.

3.

The user has set the role as “administrator” in the DUCC Preferences page. This is a safeguard so that
administrators who are also users are less likely to inadvertently affect other people’s jobs.

Control

Currently DUCC supports a single administrative control function via the web server: Stop new job submissions
and re-enable them. If submissions are blocked, all existing work runs normally, but no new work is
accepted.

8.9.2 Broker

8.9.3 Classes

This page shows the definitions of the DUCC scheduling classes. The scheduling classes are discussed in more detail in the
Resource Manager section.

8.9.4 Daemons

This page shows the current state of all DUCC processes. By default, only the administrative processes, Broker, Database,
Orchestrator, ProcessManager, ResourceManager, ServiceManager, and Webserver are shown. A button in the upper left of
the page titled “Show Agents” enables display of the status of all the DUCC agents as well. (Agents are suppressed by
default because the page is expensive to render for large systems.)

The columns shown on this page include

Status

This indicates whether the daemon is running and broadcasting state up, or not down.

All DUCC daemons broadcast a heartbeat containing process state. If the Status is down, either the daemon is
not functioning, or something is preventing state from reaching the web server via DUCC’s ActiveMQ instance.

Daemon Name

This is the name of the process.

Boot Time

This shows the date and time of the latest boot of the specific process.

Host IP

This is the IP address of the processor where the process is running.

Host Name

This shows the hostname of the processor where the process is running.

PID

This is the Unix process Id of the DUCC process.

Publication Size (last)

This shows the size of the most recent state publication of the process, in bytes.

Publication Size (max)

This shows the size of the largest state publication of the process, in bytes.

Heartbeat (last)

This shows the number of seconds since the last state publication for the process. Large numbers here indicate
potential cluster or DUCC problems.

Heartbeat (max)

This shows the longest delay since a state publication for the process was received at the web server. Large
numbers here indicate potential cluster or DUCC problems.

Heartbeat (max) TOD

This shows the time the longest delay of a state publication occurred.

JConsole URL

This is the jconsole URL for the process.

8.9.5 Machines

This page shows the states of all the machines (nodes) in the DUCC cluster.

The columns shown on this page include

Status

This shows the current state of a machine. Values include:

defined

The node is in the DUCC nodes file, but no DUCC process has been started there, or else there is a
communication problem and the state messages are not being delivered.

up

The node has a DUCC Agent process running on it and the resource manager is receiving regular heartbeat
packets from it.

down

The node had a healthy DUCC Agent on it at some point in the past (since the last DUCC boot), but
the resource manager has stopped receiving heartbeats from it.

The agent may have been manually shut down, may have crashed, or there may be a communication
problem.

Additionally, very heavy loads from jobs running the the node can cause the DUCC Agents heartbeats to
be delayed.

IP

This is the IP address of the node.

Name

This is the hostname of the node.

Nodepool

This is the host nodepool.

Memory(GB) usable

This is the amount of usable memory, in GB, as reported by each machine. This is the maximum amount that can be
allocated by the resource manager.

Usually the amount will be slightly less than the installed memory. This is because a small bit of memory is usually
reserved by the hardware for its own purposes. For example, a machine with 48GB of installed memory may report only
47GB available.

Memory(GB) free

This is the amount of free memory, in GB, as reported by each machine. This is the amount not presently allocated by
the resource manager.

CPU

This is the host CPU one minute load average.

Swap(GB) inuse

This is the total size in-use swap data. DUCC shows any value greater than 0 in red as swapping can very significantly
slow applications. However, swap use does not always mean there is a performance problem. This is flagged by DUCC
simply as an alert of a potential problem

Swap(GB) free

This is the total size of swap area.

C-Groups

If on then C-Groups are in use and processes deployed by DUCC will be limited in resource consumption.

Alien PIDs

This shows the number of processes not owned by DUCC, the operating system, or jobs scheduled on each node. The
Unix Process IDS of these processes is displayed in a hover.

DUCC preconfigures many of the standard operating system processes and userids for exclusion. These exclusion lists
are specified specified by ducc.agent.rogue.process.exclusion.filter and ducc.agent.rogue.process.user.exclusion.filter
respectively in ducc.properties and may be updated by each installation.

A common cause of alien PIDs is errant process run in unmanaged reservations. A user may reserve a machine for use
as a sandbox. If the reservation is released without properly terminating all the processes, they may linger. When
DUCC schedules the node for other purposes, significant performance penalties may be paid due to competition
between the legitimately scheduled work and the leftover “alien” processes. The purpose of this column is to bring
attention to this situation.

Heartbeat(last)

This shows the number of seconds since the last agent heartbeat from this machine.

8.10 Visualization

This page shows a visualization of all scheduled work. Every host is represented by a square whose area is proportional to the
amount of memory on the host. If work is scheduled to a host, it is represented by a rectangle whose area is proportional to
the amount of memory that is scheduled for the work. In a multi-user environment, each userid is mapped into a different
color, making it possible to see the usage per-user.

Hovers are provided to show the real memory size of each host, the schedulable memory for each host, and the amount of
memory scheduled for each bit of work.

If multiple allocations are made on a single host for the same job or service, the rectangles are combined into a single
rectangle, reducing clutter and better showing the actual usage of the job (or service).

Clicking on any box representing scheduled work sends the browser to the details page for the corresponding
work.

The screenshot below shows a visualization with a handful of 127GB hosts, 48GB hosts, and 32GB hosts. Regular UIMA-AS
jobs show as untextured boxes; for example, job 6080, owned by user Hilaria, running in a 37GB allocation in host
bluej291-41 which is a 127GB host.

Hosts bluej291-45 and 291-46 are running Managed Reservations, which are shown with crosshatches from lower-left to upper
right.

Result is JSON comprising system and user properties sets, with format similar to the above.

Part IIIProgramming Model And Applications

Chapter 9Building and Testing Jobs

9.1 Overview

A DUCC job consists of two process types, a Job Driver (JD) and one or more Job Processes (JPs). These processes
communicate via HTTP. The Job Driver process wraps the job’s Collection Reader (CR). The CR function is to define the
set of Work Items to be processed. The Collection Reader provides a small CAS for each Work Item containing a reference to
the Work Item data. The Job Processes request Work Item CASes from the Job Driver via HTTP and present them to the
job’s analytic pipeline.

A basic job’s analytic pipeline consists of an Aggregate Analysis Engine comprised by the user specified CAS Multiplier
(CM), Analysis Engine (AE) and CAS Consumer (CC) components, along with a built-in DUCC Flow Controller. The Work
Item CAS is typically sent only to the CM and returned by the Job Process when all child CASes produced by the CM have
completed processing; optionally the CR can configure Work Item CAS flow to go to the CC or to the AE & CC to complete
all processing for that Work Item.

Note:

Although the Job Driver will receive back the Work Item CAS, there is no provision for any user code to
receive the CAS. Therefore a Job Process typically adds no results to a Work Item CAS.

9.1.1 Basic Job Process Threading Model

In addition to the pipeline definition of explicitly named CM, AE and CC components, the job specification also includes the
number of pipeline threads to run in each Job Process (using the job specification parameter: process_pipeline_count). Each
pipeline thread receives Work Items independently.

DUCC creates an aggregate descriptor for the pipeline, and then creates a Deployment Descriptor for the Job Process which
specifies the number of synchronous pipelines.

9.1.2 Alternate Pipeline Threading Model

Alternately a Job Process can be fully specified by a user submitted UIMA-AS Deployment Descriptor. Thus any UIMA-AS
service deployment can be used as a Job Process. Here the parameter process_pipeline_count just defines how many Work
Items CASes will be sent to each Job Process concurrently.

Note:

In general a UIMA-AS service may be configured to return child CASes; although child CASes returned from
a Job Process will be ignored by the Job Driver, there may be significant overhead in wasted serialization and
I/O.

Another approach is to use the External Configuration Parameter Overrides mechanism in core UIMA. External overrides is
the only approach available for jobs submitted with a Deployment Descriptor.

9.2 Collection Segmentation and Artifact Extraction

UIMA is built around artifact processing. A classic UIMA pipeline starts with a Collection Reader (CR) that defines
collection segmentation, extracts the artifacts to be analyzed and puts them into the CASes to be delivered to subsequent
analytic components. A CR designed for a specific data collection is highly reusable for many different analytic
scenarios.

A single CR supplying artifacts to a large number of analysis pipelines would be a bottleneck. Not only would artifact data
need to be transported twice across the compute cluster, but analysis results would be uselessly returned to the Job Driver.
To solve both of these problems, in a DUCC job the CR only sends a reference to the artifacts in the Work Item CAS, and
artifact data is read directly by the analysis pipeline.

In DUCC collection processing the role of collection segmentation is implemented by the CR run in the Job Driver, while
artifact extraction and CAS initialization are implemented in the Cas Multiplier (CM) run in the Job Process. The
combination of a CR and associated CM should be highly reusable.

Note:

In many cases it is useful to reference multiple artifacts in a Work Item CAS. Both DUCC sample applications
described below exhibit this design.

9.3 CAS Consumer Changes for DUCC

CAS Consumers in a UIMA pipeline may require changes for scale out into DUCC jobs, to avoid scale out bottlenecks, to
preserve collection level processing, or to flush results at end-of-work-item processing.

Federated output:

Scaled out DUCC jobs distribute artifact processing to multiple pipeline instances. All instances
of a CAS Consumer should have independent access to the output target (filesystem, service, database, etc.).

Singleton processing:

Collection level processing requiring that all results go to a singleton process would usually
be done as a follow-on job, allowing incremental progress; Job Process errors due to data-dependent analysis
bugs can often be fixed without invalidating completed Work Items, enabling a restarted job to utilize the
progress made by previous job runs.

Flushing cached data:

In some scenarios each Work Item delivered to a pipeline can be considered an independent
collection. If a CAS Consumer caches data which needs to be flushed after processing the last artifact for a
Work Item, the Work Item CAS can be routed to the CAS Consumer after the last artifact CAS is processed
and used to trigger cache flushing.

9.4 Job Development for an Existing Pipeline Design

Assuming that an existing job input-output design (CR, CM, CC) is to be reused, job development is focused on
the Analysis Engine (AE) to be plugged in. Before deploying a new AE in a multithreaded Job Process it
is best to run it single threaded (process_pipeline_count=1) to separate basic logic errors from threading
problems.

To debug a Job Process with eclipse, first create a debug configuration for a ”remote java application”, specifying
”Connection Type = Socket Listen” on some free port P. Start the debug configuration and confirm it is listening on the
specified port. Then add to the job specification process_debug=port, where port is the value P used in the running debug
configuration.

When the process_debug parameter is specified, DUCC will only run a single Job Process that will connect back to the
eclipse debug configuration.

9.5 Job Development for a New Pipeline Design

A DUCC job is a UIMA application comprised of user code broken into a Collection Reader running in the Job Driver and
an Aggregate Analysis Engine (analysis pipeline) running in one or more Job Processes. Each Job Process may run multiple
instances of the pipeline, each in a different thread. The major components of the basic Job Process application are as
follows:

User Collection reader - segments the input collection in to Work Items

User CAS Multiplier - inputs a Work Item and segments it into artifacts (CASes)

User Analysis Engine - processes the CASes

User CAS Consumer - outputs results for each Work Item

DUCC built-in Flow Controller - routes Work Item CASes to the CM and optionally to the CC or AE & CC.

It is good if the CR+CM+CC combination can be reused for a broad range of AE.

9.5.1 Collection Reader (CR) Characteristics

A DUCC Job CR sends Work Item CASes to the Job Processes. These CASes contain references to the data to be read by
the Job Processes. Typically the CR Type System will be very small; in the DUCC sample applications the CR Type System
only contains the Workitem Feature Structure described below.

Note:

It is important not to include the analytic Type System in the CR. These Type Systems can be quite large
and will significantly increase the size of each Work Item CAS. The Job Driver process maintains a CAS pool
which must be as large as the total number of processing threads active in a job.

9.5.2 DUCC built-in Flow Controller

This flow controller provides separate flows for Work Item CASes and for CASes produced by the CM and/or AE. Its
behavior is controlled by the existence of a CM component, and then further specified by the org.apache.uima.ducc.Workitem
feature structure in the Work Item CAS.

When no CM is defined the Work Item CAS is simply delivered to the AE, and then to the CC if defined. Any CASes created
by the AE will be routed to the CC.

With a defined CM, the Work Item CAS is delivered only to the CM, and then returned from the JP when processing of all
child CASes created by the CM and AE has completed. Work Item CAS flow can be further refined by the CR by creating a
org.apache.uima.ducc.Workitem feature structure and setting the setSendToLast feature to true, or by setting the
setSendToAll feature to true.

9.5.3 Workitem Feature Structure

In addition to Work Item CAS flow control features, the WorkItem feature structure includes other features that are useful
for a DUCC job application. Here is the complete list of features:

sendToLast

(Boolean) - indicates the Work Item CAS be sent to the CC

sendToAll

(Boolean) - indicates Work Item CAS be sent to the AE and CC

inputspec

(String) - reference to Work Item input data

outputspec

(String) - reference to Work Item output data

encoding

(String) - useful for reading Work Item input data

language

(String) - used by the CM for setting document text language

bytelength

(Integer) - size of Work Item

blockindex

(Integer) - used if a Work Item is one of multiple pieces of an input resource

blocksize

(Integer) - used to indicate block size for splitting an input resource

lastBlock

(Boolean) - indicates this is the last block of an input resource

9.5.4 Deployment Descriptor (DD) Jobs

Job Processes with arbitrary aggregate hierarchy, flow control and threading can be fully specified via a UIMA AS
Deployment Descriptor. The Job Process uses a container which employs a UIMA-AS client to send a JMS message
comprising each CAS to the service via an internal broker.

9.5.5 Debugging

It is best to develop and debug the interactions between job application components as one, single-threaded UIMA aggregate.
DUCC provides an easy way to accomplish this, for both basic and DD job models, using the all_in_one specification
parameter.

all_in_one=local

When set to local, all Job components are run in the same single-threaded process, on the same
machine as eclipse.

all_in_one=remote

With remote, the single-threaded process is run on a DUCC worker machine as a DUCC
Managed Reservation.

To debug an all_in_one job with eclipse, first create a debug configuration for a ”remote java application”, specifying
”Connection Type = Socket Listen” on some free port P. Start the debug configuration and confirm it is listening on the
specified port. Then, before submitting the all_in_one job, add the argument process_debug=port, where port is the value P
used in the running debug configuration.

Chapter 10Sample Application: Raw Text Processing

10.1 Application Function and Design

This application expects as input a directory containing one or more flat text files, uses paragraph boundaries to segment the
text into separate artifacts, processes each artifact with the OpenNlpTextAnalyzer, and writes the results as compressed
UIMA CASes packaged in zip files. Paragraph boundaries are defined as two or more consecutive newline
characters.

By default each input file is a Work Item. In order to facilitate processing scale out, an optional blocksize parameter can
be specified that will be used to break larger files into multiple Work Items. Paragraphs that cross block
boundaries are processed in the block where they started. An error is thrown if a paragraph crosses two block
boundaries.

An output zip file is created for each Work Item. The CAS compression format is selectable as either ZIP compressed
XmiCas or UIMA compressed binary form 6 format. When compressed binary is used, each zip file also contains the full
UIMA Type System in ZIP compressed text. CASes in UIMA compressed binary form 6 format have the same
flexibility as an XmiCas in that they can be deserialized into a CAS with a different, but compatible Type
System.

By default any previously completed output files found in the output directory are preserved. While Work Item processing is
in progress the associated output files have ”_temp” appended to their filenames, and any such incomplete output files are
always ignored for subsequent jobs.

10.2 Configuration Parameters

The Collection Reader for this job is the DuccJobTextCR. It has the following configuration parameters:

For reference the source code for DUCC sample applications is in $DUCC_HOME/examples/src, with descriptors in
$DUCC_HOME/examples/sampleapps/descriptors.

10.4 Download and Install OpenNLP

Download the OpenNLP source distribution from http://opennlp.apache.org and follow the directions in the UIMAIntegration section of the included documentation to build the UIMA pear file. Then install the UIMA pear file in a directory
(which we will refer to below as $OPENNLP_HOME) with the runPearInstaller script and test it with the UIMA Cas Visual
Debugger application.

A small modification of the installed OpenNLP descriptor file is necessary for DUCC to run the component
multithreaded. Edit opennlp.uima.OpenNlpTextAnalyzer/desc/OpenNlpTextAnalyzer.xml and change the setting for
multipleDeploymentAllowed from false to true.

10.5 Get some Input Text

Choose one or more flat text files in UTF8 format that only use newline characters, not CR-LF sequences. The
text should be big enough to see the impact of DUCC job scale out. We used test data from gutenberg.org
at

http://www.gutenberg.org/ebooks/search/?sort_order=downloads

downloading ’Plain Text UTF-8’ versions of Moby Dick, War and Peace and The Complete Works of WilliamShakespeare as flat text files in a subdirectory ‘Books’, and removing all ’CR’ characters (0xD) as well as extraneous
text.

10.6 Run the Job

The job specification, DuccRawTextSpec.job, uses placeholders to reference the working directory and various operational
components located there. As run below the placeholders are resolved from environmental variables.

Note:

The classpath for the application, defined in DuccRawTextSpec.job, requires that environmental parameters
$UIMA_HOME and $OPENNLP_HOME are pointing at a valid UIMA SDK and the installed OpenNLP
PEAR file, respectively.

The total size of the three txt files is 9.4Mbytes and with a blocksize of 100000 there are 100 Work Items. Each Job Process
is configured to run 8 parallel OpenNLP pipelines. To examine the performance of processing with just a single Job Process,
the job can be submitted as:

10.7 Job Output

There will be an output zipfile for every Work Item, with zipfiles containing a compressed CAS for each document
(paragraph) found in a Work Item. If UseBinaryCompression=true each zipfile will also contain the TypeSystem for the
CASes. This is needed when deserializing these CASes into a different TypeSystem.

DuccTextCM finds 19245 paragraphs in the three text files. If the output CASes are stored as 19245 uncompressed XMI files,
the total size is 911MB. Using the default ZIP compressed XMI format and packed into 100 Work Item zip files, the
total size is 165MB, a 5.5x compression. Using UIMA binary compressed format further reduces total size to
62MB.

This output data will be used as input data for the following CAS input processing sample application.

10.8 Job Performance Details

DUCC captures a number of process performance metrics. Figure 10.1 shows details on the JD and single JP processes. The
%CPU time shown, 728, is lower than the actual because the Job Process was idle for some time before it received the first
Work Item and also idle between finishing the last Work Item and being shut down. DUCC shows the JVM spent a total of
58 seconds in GC (garbage collection), had no major page faults or page space, and used a max of 2.1GB of
RSS.

Figure 10.1: OpenNLP Process Measurements

On the Performance tab, DUCC shows the breakdown of clock time spent in each primitive UIMA component running in the
Job Process. See Figure 10.2. Processing time was dominated by the Parser component at 76.7%. The time
spent compressing and writing out CASes was 0.5%, and the time reading the input text files well below
0.1%.

Figure 10.2: OpenNLP Process Breakdown

Chapter 11Sample Application: CAS Input Processing

11.1 Application Function and Design

The main purpose of this application is to demonstrate the overhead of processing a collection of CASes grouped into zipfiles
and stored as ZIP compressed XmiCas or with UIMA compressed binary form 6 format.

Note:

This application depends on successful processing of the work in the previous chapter.

11.2 Configuration Parameters

The Collection Reader for this job is the DuccJobCasCR. It has the following configuration parameters:

InputSpec

path to directory containing input files (named InputSpec in the hope that more options will
be added).

OutputDirectory

path to directory for output files.

IgnorePreviousOutput

(optional) boolean to ignore (overwrite) previous output files.

SendToLast

(optional) boolean to route WorkItem CAS to last pipeline component. Set to true in this
application.

SendToAll

(optional) boolean to route WorkItem CAS to all pipeline components. Not used in this
application.

The CAS Consumer is the DuccCasCC and has the following configuration parameters:

XmiCompressionLevel

(optional) compression value if using ZIP compression. Default is 7.

UseBinaryCompression

(optional) boolean to select UIMA binary CAS compression.

11.3 Run the Job

The job specification, DuccCasInputSpec.job, uses placeholders to reference the working directory and various
operational components located there. As run below the placeholders will be resolved from environmental
variables.

Note:

The classpath for the application, defined in DuccCasInputSpec.job, requires that environmental parameters
$UIMA_HOME and $OPENNLP_HOME are pointing at a valid UIMA SDK and the installed OpenNLP
PEAR file, respectively.

11.4 Job Performance Details

Figure 11.1 shows the component breakdown using binary CAS compression. Reading and deserializing took 38% vs the
60% spent serializing and writing. Using 8 pipeline threads in one process the 19245 CASes output from the last application
were read and re-written in 9 seconds.

Figure 11.1: CAS Input Processing Performance

11.5 Limiting Job Resources

Although this 8-threaded Job Process was primarily CPU bound doing serialization work, it is possible to become
I/O bound with enough threads banging on a shared filesystem. DuccCasInputSpec.job demonstrates how to
limit the total number of processing threads to 32 using the combination of process_pipeline_count=8 and
process_deployments_max=4.

I/O vs CPU bottlenecks can be detected using the detailed performance job data reported by DUCC and comparing results
with various levels of scale out.

Part IVDucc Administrators Guide

Chapter 12Installation, Configuration, and Verification

12.1 Overview

DUCC is a multi-user, multi-system distributed application. For first-time users a staged installation/verification
methodology is recommended, roughly as follows:

Single system installation - single node - all work runs with the credentials of the installer.

Optionally add worker nodes to the cluster.

Enable CGroup containers. CGroups protect DUCC managed processes running on the same machine from
inappropriately stealing memory or CPU resources from each other. CGroups are also required for DUCC to
measure and report performance metrics on managed processes.

Enable multiple-user support - processes run with the credentials of the submitting user, while DUCC runs as
user ducc. This step requires root authority on one or more machines.

Nominally user ducc runs the DUCC software. However another user, for example duccster, could be chosen. In this
document references to user ducc will mean to the user that you have chosen, be it ducc or duccster or some other. The
chosen user is the OS user installing DUCC.

When upgrading from an existing installation the ducc_update script may be used to replace the system files while leaving the
site-specific configuration files in place. For more information see ducc_update.

Since with this release the persistence data about completed work is stored in a database, additional upgrade steps are
required to convert the older file-based data in order to preserve information about past work. For more information see
db_create and db_loader.

DUCC is distributed as a compressed tar file. If building from source, this file will be created in your svn trunk/target
directory. The distribution file is in the form

uima-ducc-[version]-bin.tar.gz

where [version] is the DUCC version; for example, uima-ducc-2.1.0-bin.tar.gz. This document will refer to the distribution file
as the “<distribution.file>”.

12.2 Software Prerequisites

Note: On some systems the default user limits for max user processes (ulimit -u) and nfiles (ulimit -n) are
defined too low for DUCC. The shell login profile for user ducc should set the soft limit for max user processes
to be the same as the hard limit (ulimit -u ‘ulimit -Hu‘), and the nfiles limit raised above 1024 to at least twice
the number of user processes running on the cluster.

Python 2.x, where ’x’ is 4 or greater. DUCC has not been tested on Python 3.x.

Java JDK 7 or 8. DUCC has been tested and run using IBM and Oracle JDK 1.7 & 1.8. A JDK is required by
DUCC’s web server for JSP compilations, for which a JRE is insufficient.

Passwordless ssh for the userid running DUCC

Additional requirements for multiple system installation:

All systems must have a shared filesystem (such as NFS or GPFS) and common user credentials. The
$DUCC_HOME directory must be located on a shared filesystem.

Additional requirements for running multiple user processes with their own credentials.

A userid ducc, and group ducc. User ducc must be the only member of group ducc.

DUCC installed and run with user ducc credentials.

Note: With these restrictions any userid can be configured to be the DUCC user and group.

Root access is required to setuid-root the DUCC process launcher.

Additional requirements for CGroup containers:

A userid ducc, and group ducc. User ducc must be the only member of group ducc.

DUCC installed and run with user ducc credentials.

Note: With these restrictions any userid can be configured to be the DUCC user and group.

Root access is required to configure and enable a custom cgroup for DUCC.

A running cgroup subsystem. True by default for newer OS.

Create a custom cgroup definition that the DUCC user can use to run managed applications in. The custom
definition to go into /etc/cgconfig.conf is described in CGroups Installation and Configuration.

The cgroup tools package, e.g. libcgroup-tools on centos and cgroup-tools on ubuntu.

12.3 Building from Source

To build from source, ensure you have Subversion and Maven installed. Extract the source from the SVN repository named
above.

Then from your extract directory into the root directory (usually current-directory/trunk), and run the command

mvn install

or

mvn install -Pbuild-duccdocs

if you have LaTeX installed and wish to do the optional build of documentation. The build-duccdocs profile can also
activated if the environment valiable BUILD_DUCCDOCS is set true.

Note: LaTeX output is quite verbose and it is suppressed when run via maven.

An alternative approach for modifying DUCCDOCS is to use the LaTeX commands manually. Not only is the build much
faster, it also exposes LaTeX error messages lost by the suppression. To build duccbook.html manually and leave the output
in the same directory:

Note: The manual command needs to be run twice if modifications have been made that affect internal bookreferences such as the table of contents. Also, temporary files created by LaTeX will need to be cleaned upmanually.

If this is your first Maven build it may take quite a while as Maven downloads all the open-source pre-requisites. (The
pre-requisites are stored in the Maven repository, usually your $HOME/.m2).

When build is complete, a tarball is placed in your current-directory/trunk/target directory.

12.4 Documentation

After installation the DUCC documentation is found (in both PDF and HTML format) in the directory ducc_runtime/docs.
As well, the DUCC webserver contains a link to the full documentation on each major page. The API is documented only via
JavaDoc, distributed in the webserver’s root directory $DUCC_HOME/webserver/root/doc/api.

If building from source, Maven places the documentation in

trunk/uima-ducc-duccdocs/target/site (main documentation), and

trunk/target/site/apidocs (API Javadoc)

12.5 Single System Installation and Verification

Any user ID can be used to run a single-system DUCC, but “ducc” userid is recommended. This user will employ cgroups as
well as launching and running processes with the credentials of the submitting user.

If multiple nodes are going to be added later, the ducc runtime tree should be installed on a shared filesystem so that it can
be mounted on the additional nodes.

Verification submits a very simple UIMA pipeline for execution under DUCC. Once this is shown to be working, one may
proceed installing additional features.

12.6 Minimal Hardware Requirements for Single System Installation

One Intel-based or IBM Power-based system (Big or Little Endian). (More systems may be added later.)

8GB of memory. 16GB or more is preferable for developing and testing applications beyond the non-trivial.

1GB disk space to hold the DUCC runtime, system logs, and job logs. More is usually needed for larger
installations.

Please note: DUCC is intended for scaling out memory-intensive UIMA applications over computing clusters consisting of
multiple nodes with large (16GB-256GB or more) memory. The minimal requirements are for initial test and evaluation
purposes, but will not be sufficient to run actual workloads.

12.7 Single System Installation

1.

Expand the distribution file with the appropriate umask:

(umask 022 && tar -zxf <distribution.file>)

This creates a directory with a name of the form “apache-uima-ducc-[version]”.

This directory contains the full DUCC runtime which you may use “in place” but it is highly recommended
that you move it into a standard location on a shared filesystem; for example, under ducc’s HOME
directory:

mv apache-uima-ducc-[version] /home/ducc/ducc_runtime

We refer to this directory, regardless of its location, as $DUCC_HOME. For simplicity, some of the examples in this
document assume it has been moved to /home/ducc/ducc_runtime.

2.

Change directories into the admin sub-directory of $DUCC_HOME:

cd $DUCC_HOME/admin

3.

Run the post-installation script:

./ducc_post_install

If this script fails, correct any problems it identifies and run it again.

Note that ducc_post_install initializes various default parameters which may be changed later by the system
administrator. Therefore it usually should be run only during this first installation step.

4.

If you wish to install jconsole support from the webserver, make sure Apache Ant is installed, and run

./sign_jconsole_jar

This step may be run at any time if you wish to defer it.

That’s it, DUCC is installed and ready to run. (If errors were displayed during ducc_post_install they must be corrected
before continuing.)

12.8 Initial System Verification

Here we verify the system configuration, start DUCC, run a test Job, and then shutdown DUCC.

To run the verification, issue these commands.

1.

cd $DUCC_HOME/admin

2.

./check_ducc

Examine the output of check_ducc. If any errors are shown, correct the errors and rerun check_ducc until there
are no errors.

3.

Finally, start ducc: ./start_ducc

Start_ducc will first perform a number of consistency checks. It then starts the ActiveMQ broker, the DUCC control
processes, and a single DUCC agent on the local node.

Now open a browser and go to the DUCC webserver’s url, http://<hostname>:42133 where <hostname> is the name of the
host where DUCC is started. Navigate to the Reservations page via the links in the upper-left corner. You should see the
DUCC JobDriver reservation in state WaitingForResources. In a few minutes this should change to Assigned. Now jobs can
be submitted.

12.8.1 Submitting a test job

Open the browser in the DUCC jobs page. You should see the job progress through a series of transitions: Waiting For
Driver, Waiting For Services, Waiting For Resources, Initializing, and finally, Running. You’ll see the number of work items
submitted (15) and the number of work items completed grow from 0 to 15. Finally, the job will move into Completing and
then Completed..

Since this example does not specify a log directory DUCC will create a log directory in your HOME directory
under

$HOME/ducc/logs/job-id

In this directory, you will find a log for the sample job’s JobDriver (JD), JobProcess (JP), and a number of other files
relating to the job.

This is a good time to explore the DUCC web pages. Notice that the job id is a link to a set of pages with details about the
execution of the job.

Notice also, in the upper-right corner is a link to the full DUCC documentation, the “DuccBook”.

12.8.2 Registering a test service

First start an application broker using the UIMA-AS script included in the DUCC installation, see UIMA-AS broker. Then in
another shell define the broker URL using the name of the host the broker was started on, and register the service. On your
browser select the Services page and wait for the service to become Available.

12.8.3 To stop DUCC

12.9 Add additional nodes to the DUCC cluster

$DUCC_HOME must be on a shared filesystem and mounted at the same location on all DUCC nodes.

If user’s home directories are on local filesystems the location for user logfiles should be specified to be on a shared
filesystem.

Addional nodes are normally added to a worker node group. Note that the DUCC head node does not have to be a worker
node. In addition, the webserver node can be separate from the DUCC head node (see webserver configuration options in
ducc.properties).

For worker nodes DUCC needs to know what node group each machine belongs to, and what nodes need an Agent process to
be started on.

The configuration shipped with DUCC have all nodes in the same ”default” node pool. Worker nodes are listed in the
file

$DUCC_HOME/resources/ducc.nodes.

During initial installation, this file was initialized with the node DUCC is installed on. Additional nodes may be added to the
file using a text editor to increase the size of the DUCC cluster.

DUCC launches user processes through ducc_ling, a small native C application. By default the resultant process runs with
the credentials of the user ID of the DUCC application. It is possible for multiple users to submit work to DUCC in this
configuration, but it requires that the user ID running DUCC has write access to all directories to which the user process
outputs data. By configuring the ducc user ID and ducc_ling correctly, work submitted by all users will run with their own
credentials.

Before proceeding with this step, please note:

The sequence operations consisting of chown and chmod MUST be performed in the exact order given below.
If the chmod operation is performed before the chown operation, Linux will regress the permissions granted by
chmod and ducc_ling will be incorrectly installed.

ducc_ling is designed to be a setuid-root program whose function is to run user processes with the identity of the submitting
user. This must be installed correctly; incorrect installation can prevent jobs from running as their submitters, and in the
worse case, can introduce security problems into the system.

ducc_ling can either be installed on a local disk on every system in the DUCC cluster, or on a shared-filesystem that does not
suppress setuid-root permissions on client nodes. The path to ducc_ling must be the same on each DUCC node. The default
path configuration is $DUCC_HOME/admin/${os.arch}/ in order to handle clusters with mixed OS platforms.
${os.arch} is the architecture specific value of the Java system property with that name; examples are amd64 and
ppc64.

The steps are: build ducc_ling for each node architecture to be added to the cluster, copy ducc_ling to the
desired location, and then configure ducc_ling to give user ducc the ability to spawn a process as a different
user.

In the example below ducc_ling is left under $DUCC_HOME, where it is built.

As user ducc, build ducc_ling for necessary architectures (this is done automatically for the DUCC head machine by the
ducc_post_install script). For each unique OS platform:

1.

cd $DUCC_HOME/admin

2.

./build_duccling

Then, as user root on the shared filesystem, cd $DUCC_HOME/admin, and for each unique OS architecture:

chmod 4750 ${os.arch}/ducc_ling (ducc_ling runs as user root when started by users in group ducc)

If these steps are correctly performed, ONLY user ducc may use the ducc_ling program in a privileged way. ducc_ling
contains checks to prevent even user root from using it for privileged operations.

If a different location is chosen for ducc_ling the new path needs to be specified for ducc.agent.launcher.ducc_spawn_path in
$DUCC_HOME/resources/site.ducc.properties. For more information see Properties merging.

12.11 CGroups Installation and Configuration

Note:

A key feature of DUCC is to run user processes in CGroups in order to guarantee each process always has
the amount of RAM requested. RAM allocated to the managed process (and any child processes) that exceed
requested DUCC memory size will be forced into swap space. Without CGroups a process that exceeds its
requested memory size by N% is killed (default N=5 in ducc.properties), and memory use by child processes is
ignored.

DUCC’s CGroup configuration also allocates CPU resources to managed processes based on relative memory
size. A process with 50% of a machine’s RAM will be guaranteed at least 50% of the machine’s CPU resources
as well.

Note: if CGroups is not installed on a machine the DUCC Agent will detect this and not attempt to use the feature. CGroups
can also be disabled for all machines or for individual machines. Use ducc.agent.launcher.cgroups.enable and
ducc.agent.exclusion.file respectively in site.ducc.properties.

12.12 Full DUCC Verification

This is identical to initial verification, with the one difference that the job “1.job” should be submitted as any user other
than ducc. Watch the webserver and check that the job executes under the correct identity. Once this completes, DUCC is
installed and verified.

12.13 Enable DUCC webserver login

This step is optional. As shipped, the webserver is disabled for logins. This can be seen by hovering over the Login text
located in the upper right of most webserver pages:

System is configured to disallow logins

To enable logins, a Java-based authenticator must be plugged-in and the login feature must be enabled in the ducc.properties
file by the DUCC administrator. Also, ducc_ling should be properly deployed (see Ducc_ling Installation section
above).

A beta version of a Linux-based authentication plug-in is shipped with DUCC. It can be found in the source
tree:

org.apache.uima.ducc.ws.authentication.LinuxAuthenticationManager

The Linux-based authentication plug-in will attempt to validate webserver login requests by appealing to the host OS. The
user who wishes to login provides a userid and password to the webserver via https, which in-turn are handed-off to the OS
for a success/failure reply.

To have the webserver employ the beta Linux-based authentication plug-in, the DUCC administrator should perform the
following as user ducc:

Note: The beta Linux-based authentication plug-in has limited testing. In particular, it was tested using:

Red Hat Enterprise Linux Workstation release 6.4 (Santiago)

A beta version of a File-based authentication plug-in is shipped with DUCC. It can be found in the source
tree:

org.apache.uima.ducc.ws.authentication.SecureFileAuthenticator.java

The File-based authentication plug-in will attempt to validate webserver login requests by checking againist a file that only
the user can view, either in the security directory specified in ducc.properties, else in the user home directory. The user who
wishes to login provides a userid and password to the webserver via https, which in-turn are checked against the file-based
password for a success/failure reply.

Each time a login is attempted by the user, a new password is generated in the secure file. Thus, each login password is single
use.

To have the webserver employ the beta File-based authentication plug-in, the DUCC administrator should perform the
following as user ducc:

With these settings, users will be required to login to the DUCC Web Server to view user data (e.g. user log files). In
addition, user data will be transported over https only.

There is a list of exempted URIs for which transport over http is allowed:

$DUCC_HOME/webserver/etc/http-uri-encryption-exemption.list

The exemption list allows, for example, the

ducc_monitor

to fetch status over http:

ducc-servlet/proxy-job-monitor-report

12.15 DUCC daemons monitoring and notification

$DUCC_HOME/bin/ducc_watcher is a Python script that, when run, contacts the
DUCC Web Server to fetch data and determine the status of the critical head node daemons.
It can be run as a cron job to detect down daemons and send email notifications
to a list of receipients specified via command invocation option.

Use the --help options for details.

Purpose: send e-mail when a DUCC daemon state changes to not up

Files created by script:
- /tmp/<user>/ducc_watcher.state
+ comprises the last recorded state of DUCC daemons

- /tmp/<user>/ducc_watcher.log
+ comprises a log produced by the script

Chapter 13Administration

13.1 WebServer Authentication

By default, DUCC is configured such that there is effectively no authentication enforcement by the WebServer.
No password entry is permitted on the Login panel and any userid specified is accepted whether it exists or
not.

To enable your own authentication measures, you should perform the following steps:

Note: When a user clicks on the WebServer Login link, the login dialog is shown. On that dialog panel is shown the
authenticator: version, which is supplied by your authentication manager implementation’s getVersion() method. Also shown
are boxes for userid and password entry. If your authentication manager implemenation’s isPasswordChecked() method
returns true then the password box will accept input, otherwise it will be disabled.

13.1.1 Example Implementation

Shown below is an example implementation which can be used as a template for coding protection by means of interfacing
with your site’s security measures.

In this example, the SiteSecurity Java class is presumed to be existing and available code at your installation.

13.1.4 Example ANT script to build jar

Shown below is an example ANT script to build a ducc-authenticator.jar file. The resulting jar file should be placed user
DUCC’s lib directory along with any dependency jars, and defined in ducc.properties file.

13.1.5 Example ducc.properties entries

Shown here is a snippet of the ducc.properties file defining the class to be used for authentication and the administrator
created folder site-security, which should contain the ducc-authenticator.jar you built plus any jar files upon which it
depends.

Note: the site-security directory must be located within DUCC’s lib directory.

# Site specific jars: include all jars in directory site-security
ducc.local.jars = site-security/*

13.1.6 Example ducc.administrators

Example contents of ducc.administrators file located within DUCC’s resources directory. Only userids listed here can assume
the Administrator role when performing operations via the WebServer.

jdoe
fred
hal9000

13.2 Properties

Public properties are in a primary configuration file is called ducc.properties and always resides in the directory
ducc_runtime/resources.

Private properties are in a secondary configuration file call ducc.private.properties and always resides in the directory
ducc_runtime/resources/private.

13.3 Properties merging

With DUCC 2.0.0 the shipped DUCC properties file is designed to be read-only. Installations create a local properties file
which is automatically merged with the default properties file as part of system startup.

The shipped DUCC properties file is called default.ducc.properties. This file should never be edited or modified.

The local site override properties file is called site.ducc.properties. This is a normal Java properties file containing
override and additional properties. An initial site.ducc.properties is created on installation of DUCC 2.0.0 by
ducc_post_install.

On startup (start_ducc), verification (check_ducc), and RM reconfiguration (rm_reconfigure), the two properties files are
merged, with site.ducc.properties taking preference, to create the operational file, ducc.properties, which is used by all DUCC
components. This file should not be edited as it will be over-written whenever start_ducc or check_ducc is
run.

13.4 ducc.properties

Some of the properties in ducc.properties are intended as the ”glue” that brings the various DUCC components together and
lets then run as a coherent whole. These types of properties should be modified only by developers of DUCC
itself.

Some of the properties are tuning parameters: timeouts, heartbeat intervals, and so on. These may be modified by DUCC
administrators, but only after experience is gained with DUCC, and only to solve specific performance problems. The default
tuning parameters have been chosen by the DUCC system developers to provide ”best” operation under most reasonable
situations.

Some of the properties describe the local cluster configuration: the location of the ActiveMQ broker, the location of the Java
JRE, port numbers, etc. These should be modified by the DUCC administrators to configure DUCC to each individual
installation.

13.5 default.ducc.properties

# -----------------------------------------------------------------------# Licensed to the Apache Software Foundation (ASF) under one# or more contributor license agreements. See the NOTICE file# distributed with this work for additional information# regarding copyright ownership. The ASF licenses this file# to you under the Apache License, Version 2.0 (the# "License"); you may not use this file except in compliance# with the License. You may obtain a copy of the License at## http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing,# software distributed under the License is distributed on an# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY# KIND, either express or implied. See the License for the# specific language governing permissions and limitations# under the License.# -----------------------------------------------------------------------# WARNING: DO NOT EDIT THIS FILE.# All customizations must be created in a file "site.ducc.properties" that is in# your ducc_runtime/resources. DUCC’s startup procedures will merge this file and# your site.ducc.propeties into ducc.properties which is what DUCC will use.# WARNING DO NOT EDIT THIS FILE.# ====================================================================================# This configuration file contains most of the specifications for DUCC.## Two other important customizable files define the classes and nodes.## The class definition file is specified by the property ’ducc.rm.class.definitions’# and a sample called ducc.classes has been provided in DUCC_HOME/resources.## Node definitions are by default taken from ducc.nodes but this may be overridden# with the -n option on start_ducc.## The first two entries here are customized in site.ducc.properties by ducc_post_install.## ====================================================================================# +==================================================================================================+# | General |# +==================================================================================================+# The name of the node where DUCC runs.# This property declares the node where the DUCC administrative processes run (Orchestrator,# Resource Manager, Process Manager, Service Manager). This property is required and MUST be# configured in new installation. The installation script ducc_post_install initializes this# property to the node the script is executed on.ducc.head = <head-node># This property declares the nodes which may become the ducc.head.# This property is optional, but if specified then the node specified as ducc.head must also# appear in this comma separated failover list.# The failover list allows the agents (at boot time only) to configure themselves to employ# a broker on any of the listed nodes.ducc.head.failover = ${ducc.head}# The full name of the Java command.# This specifies the full path to the JVM to be used by the DUCC processes. This MUST be# configured. The installation script ducc_post_install initializes this property to# full path to java in the installer’s environment. (If the java command cannot be found,# ducc_post_install exits with error.)ducc.jvm = <full-path-to-java-command># The name of the cluster as shown by the Web Server.# This is a string used in the Web Server banner to identify the local cluster. It is used# for informational purposes only and may be set to anything desired.ducc.cluster.name=Apache UIMA-DUCC# Specify location of private resources directory. UIMA-3892ducc.private.resources = ${DUCC_HOME}/resources.private# Location of security home directory. When non-empty the userid is appended and it replaces the# default of <user.home> as the location of the keys used in request validation.ducc.security.home =# Name any site-local jars.# This may be used to list site-specific jars that are required by local# customizations, e.g. authentication. The value must be a blank-delimited list of jars# relative to the DUCC_HOME/lib directory.#ducc.local.jars =# Declare the type of middleware providing the JMS service used by DUCC.ducc.jms.provider=activemq# +==================================================================================================+# | Broker |# +==================================================================================================+#Declare the wire protocol used to communicate with ActiveMQ.ducc.broker.protocol=tcp# This declares the node where the ActiveMQ broker resides. It MUST be updated to# the actual node where the broker is running as part of DUCC installation.# The default value will not work.ducc.broker.hostname=${ducc.head}# This declares the port on which the ActiveMQ broker is listening for messages.ducc.broker.port=61617# The broker *client* url decoration (ie - DUCC daemons).ducc.broker.url.decoration=jms.useCompression=true&jms.prefetchPolicy.all=0# The Broker’s name must match the actual broker name in the broker config.# THIS IS NOT THE BROKER HOSTNAME WHICH IS CONFIGURED IN ducc.broker.hostname.# This is the internal name of the broker, used to locate Broker’s MBean in# JMX Registry. It is NOT related to any node name. When using the ActiveMQ# distribution supplied with DUCC it should always be set to localhost.ducc.broker.name=localhost# The Broker’s jmx port.# This is the port used to make JMX connections to the broker. This should only# be changed by administrators familiar with ActiveMQ configuration.ducc.broker.jmx.port=1100# If set to true, DUCC will start and stop the ActiveMQ broker as part of its normal# start/stop scripting.ducc.broker.automanage = true# This is the ActiveMQ credentials file used to authenticate DUCC daemons with the# broker.ducc.broker.credentials.file=${ducc.private.resources}/ducc-broker-credentials.properties# This sets the heap size for the broker.ducc.broker.memory.options = -Xmx1G# This is the ActiveMQ configuration file to use. The path# must be specified relative to the ActiveMQ installation directory.ducc.broker.configuration = conf/activemq-ducc.xml# This names the location where ActiveMQ is installed.ducc.broker.home = ${DUCC_HOME}/apache-uima/apache-activemq# The broker "server" URL decoration,# = 45 second timeout on write operations to the socket.ducc.broker.server.url.decoration = transport.soWriteTimeout=45000# +==================================================================================================+# | Transport |# +==================================================================================================+# To enable tracing of RM messages arriving in OR and NodeMetrics arriving in WS.#ducc.transport.trace = orchestrator:RmStateDuccEvent webserver:NodeMetricsUpdateDuccEvent# +==================================================================================================+# | Authentication |# +==================================================================================================+# This specifies the class used for Web Server session authentication.# If unconfigured, the Web Server enforces no authentication.#ducc.authentication.implementer=org.apache.uima.ducc.ws.authentication.LinuxAuthenticationManager#ducc.authentication.implementer=org.apache.uima.ducc.ws.authentication.SecureFileAuthenticator# Specify users allowed to log in to the web server.#ducc.authentication.users.include = user1 user2# Specify users not allowed to login (default is all users can login; if user is in# both include and exclude lists, then exclude is enforced)#ducc.authentication.users.exclude = user1 user3# Specify groups allowed to login (default is all groups can login)#ducc.authentication.groups.include = groupA groupB# Specify groups not allowed to login (default is all groups can login; if group is in# both include and exclude lists, then exclude is enforced)#ducc.authentication.groups.exclude = groupA groupC# +==================================================================================================+# | Language |# +==================================================================================================+# Establish the language for national language support of messages.# Currently only "en" is supported.ducc.locale.language=en# Establish the country for National Language Support of messages.# Currently only "us" is supported.ducc.locale.country=us# +==================================================================================================+# | Daemon Administration |# +==================================================================================================+# This is the JMS endpoint name used for DUCC administration messages.ducc.admin.endpoint=ducc.admin.channel# This is the JMS message type used for DUCC administration messages.# Only "topic" is supported.ducc.admin.endpoint.type=topic# JMX port number for Ducc process. Each DUCC process will attempt# to use this port for its JMX Connector. If the port is not available# port+1 will be used until an available port is found.# Every process started by DUCC has JMX enabled by default.# The DUCC WebSever’s System.Daemons page is used to find the JMX URL that gets assigned to# each of the DUCC management processes. The Web Server’s Job.Details page for each job is# used to find the JMX URL that is assigned to each JP.ducc.jmx.port=2099ducc.agent.jvm.args = -Xmx500Mducc.orchestrator.jvm.args = -Xmx1Gducc.rm.jvm.args = -Xmx1Gducc.pm.jvm.args = -Xmx1Gducc.sm.jvm.args = -Xmx1G# use the following flag under IBM Java 8 to allow Chromium to visit# w/o getting ERR_SSL_VERSION_OR_CIPHER_MISMATCH# -Dcom.ibm.jsse2.overrideDefaultTLS=true# see https://issues.apache.org/jira/browse/UIMA-5475ducc.ws.jvm.args = -Xmx2G -Djava.util.Arrays.useLegacyMergeSort=true -Dcom.ibm.jsse2.overrideDefaultTLS=true# +==================================================================================================+# | Node Administration |# +==================================================================================================+# Specify a minimum amount of free swap space available on a node.# If an agent detects free swap space dipping below the value defined# below, it will find the fattest (in terms of memory) process in its# inventory and kill it. The value of the parameter below is expressed# in bytes.# Initially disabled by setting the threshold at 0.ducc.node.min.swap.threshold=0# +==================================================================================================+# | Job Administration |# +==================================================================================================+# Max number of work-item CASes for each job (default is "unlimited")# Note: formerly known as ducc.threads.limit# This enforces a maximum number of pipelines per job, over all its processes. No# job will have more active work-items than this dispatched.# The value is related to the size of the Job Driver heap and the real memory consumed by JD.# If the JD is consuming too much memory, try reducing this value.ducc.job.max.pipelines.count = 5000# +==================================================================================================+# | CLI Administration |# +==================================================================================================+# These environment values are included on job/service/AP submissionsducc.environment.propagated = USER HOME LANG DUCC_SERVICE_INSTANCE# No timeout on CLI requestsducc.cli.httpclient.sotimeout=0#------------------------------------------------------------------------------# When set, the CLI signs each request so the Orchestrator can be sure the# requestor is actually who he claims to be.# off, // CLI submit and cancel signature enforcement disabled# on, // CLI submit and cancel signature enforcement enabled (default)ducc.signature.required=on#------------------------------------------------------------------------------# +==================================================================================================+# | Web Server |# +==================================================================================================+# The name of the pluggable java class used to implement the Web Server.ducc.ws.configuration.class=org.apache.uima.ducc.ws.config.WebServerConfiguration# This endpoint is used for Web Server self test to determine viability of broker.# After 3 missed messages to self via broker, Web Server considers broker to be down.ducc.ws.state.update.endpoint=ducc.ws.state# This is the JMS endpoint type used for the state messages sent by the Web Server.ducc.ws.state.update.endpoint.type=topic# The interval in milliseconds between Web Server publications of its state.ducc.ws.state.publish.rate=5000# The elapsed time in milliseconds between monitored head-node daemons’ publications# that if exceeded indicates "down". Default = 120000 (two minutes).ducc.ws.monitored.daemon.down.millis.expiry=120000# Optionally configure the Web Server to run on a non-head node# This is the name of the node the web server is started on. If not specified,# the web server is started on ${ducc.head}.# ducc.ws.node = my.node.com# Optionally configure the Web Server IP address# In multi-homed systems it may be necessary to specify to which of the multiple addresses# the Web Server listens for requests. This property is an IP address that specifies to which# address the Web Server listens.# ducc.ws.ipaddress = <fill in an IP address># Optionally configure the Web Server IP port for HTTP requests, default is 42133ducc.ws.port = 42133# Optionally configure the Web Server IP port for HTTPS requests, default is 42155ducc.ws.port.ssl = 42155# Optionally configure the Web Server welcome page, default is index.html (which forwards to jobs.html)ducc.ws.welcome.page = index.html# Optionally configure the Web Server job automatic cancel timeout, default is 10. To disable# feature specify 0. Employed when user specifies --wait_for_completion flag on job submission,# in which case the job monitor program must visit# http://<host>:<port>/ducc-servlet/proxy-job-status?id=<job-id> within this expiry time# else the job will be automatically canceled (unless feature disabled) by the Web Server# acting as the administrator ducc (which must be specified in the ducc.administrators file).ducc.ws.automatic.cancel.minutes = 5# Optionally configure the Web Server max cached (and thus available for display)# history entries for each of Jobs/Reservations/Servicesducc.ws.max.history.entries = 4096# Specify login enabled (default is true)ducc.ws.login.enabled = false# For node visualization - if true, strip domain names from labels for cleaner visualsducc.ws.visualization.strip.domain = true# Optionally configure the Web Server request log, default is 0 (meaning no request logging)# Logs are written to DUCC_HOME/logs/webserverducc.ws.requestLog.RetainDays = 30# Specify one of { unrestricted, encrypted, blocked } to control# requests to the Web Server with responses containing user data.# When "unrestricted" requests for user data via http or https are honored.# When "encrypted" requests for user data only via https are honored.# When "blocked" requests for user data are not honored.ducc.ws.user.data.access = unrestricted# Note: to employ "encrypted" use the following settings:# ducc.ws.port = 42133# ducc.ws.port.ssl = 42155# ducc.ws.login.enabled = true# ducc.ws.user.data.access = encrypted# See documentation for further information.# --------------------------------------------------------------# name: ducc.ws.banner.message# purpose: display banner message on all main pages# choices: default=none# change: effective immediately#ducc.ws.banner.message = Do not adjust your set. This is a message from your DUCC administrator.# +==================================================================================================+# | Job Driver |# +==================================================================================================+# The name of the pluggable java class used to implement the Job Driver (JD).ducc.jd.configuration.class=org.apache.uima.ducc.transport.configuration.jd.JobDriverConfiguration# This is the JMS endpoint name by the Job Driver to send state to the Orchestrator.ducc.jd.state.update.endpoint=ducc.jd.state# This is the JMS message type used to send state to the Orchestrator.ducc.jd.state.update.endpoint.type=topic# The interval in milliseconds between JD state publications to the Orchestrator.# A higher rate (smaller number) may slightly increase system response but will# increase network load. A lower rate will somewhat decrease system response and# lower network load.ducc.jd.state.publish.rate=15000# This is a human-readable string used to form queue names for the JMS queues used to pass# CASs from the Job Driver to the Job Processes. The completed queue named comprises the prefix# concatenated with the DUCC assigned Job number.ducc.jd.queue.prefix=ducc.jd.queue.# After dispatching a work item to UIMA-AS client for processing, the number of minutes that the# Job Driver will wait for two callbacks (queued and assigned) before considering the work item# lost. The elapsed time for the callbacks is normally sub-second. Intermittent network problems# may cause unusual spikes. If not specified, default value is 5 minutes.ducc.jd.queue.timeout.minutes=5# If not specified, default value is 24 hrs (24*60 minutes)# This property specifies the default value for the time, in minutes, that the JD should# wait for a work-item to be processed. If processing has not completed in this time the# process is terminated and the job’s error handler decides whether to retry the# work-item or not.ducc.default.process.per.item.time.max = 1440# If not specified, default max time in minutes allowed for AE initialization.# This property specifies the default value for the time, in minutes, that the agent should# wait for a JP to complete initialization. If initialization is not completed in this time# the process is terminated and and InitializationTimeout status is sent to the JD# which decides whether to retry the process or terminate the job.ducc.default.process.init.time.max = 120# The following 5 values comprise the specification used by the DUCC Orchestrator daemon to# request an allocation from the DUCC Resource Manager for Job Driver use. The values given# below are the defaults.ducc.jd.host.class=JobDriverducc.jd.host.description=Job Driverducc.jd.host.memory.size=2GBducc.jd.host.number.of.machines=1ducc.jd.host.user=System# For a newly started Job, the number of JP UIMA initialization failures# allowed until at least one JP succeeds - otherwise, the Job self-destructs.# Default is 1.ducc.jd.startup.initialization.error.limit=1# The next 4 values are related - each JD is assigned a piece of the Job Driver host memory# which, # along with the size of the CR’s type system, limits the number of active work-item# CASes in a job. To avoid swapping the max heap size should also be restricted.# Memory size in MB allocated for each JD (default 300)# When CGroups are enabled, this is the RSS, in MB, that is reserved for each JD process,# and enforced by the CGroup support. Larger JDs are permitted, but the CGroup support will# force the excess RSS onto swap. This potentially slows the performance of that JD, but# preserves the resources for other, better-behaved, JDs.ducc.jd.share.quantum = 400# The number of "slices" of size "jd.share.quantum" kept in reserve.# The Orchestrator makes Reservation requests to RM to get Reservations# (Job Driver hosts) each of which is then subdivided into "slices", one# per JD. This number specifies the number of unused "slices" that should# be kept on-hand in anticipation of newly submitted jobs (default 2).# !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!# If the value specified is 0 then no JD allocation will take place# and all submitted jobs will be rejected.# !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!ducc.jd.share.quantum.reserve.count = 3# The maximum length of a work-item name returned by CAS.getDocumentText().# Truncation is enforced beyond this limit.# If not specified, there is no limit.ducc.jd.workitem.name.maximum.length = 64# Extra JVM args to be appended to any user-supplied "driver_jvm_args"# Dynamic: changes to this property immediately affect new submitted work# Flag: -DUimaAsCasTracking will add to logs:# UIMA-AS client & service trigger internal tracing including RefId,# UIMA-AS client onBeforeMessageSendHandler callbacks including RefId, and# UIMA-AS client onBeforeProcessCAS callbacks including RefId# Flag: -DUimaAsClientTracking will add to jd.out.log:# core pool size changes,# UIMA-AS client sendAndReceive invocations,# UIMA-AS client onBeforeMessageSendHandler callbacks, and# UIMA-AS client onBeforeProcessCAS callbacks# Note: should contain an Xmx a little below the "ducc.jd.share.quantum" value# the Xmx entry is ignored if the user has specified oneducc.driver.jvm.args = -Xmx300M# Max number of threads in Jetty thread pool servicing incoming# HTTP requests# ducc.driver.jetty.max.threads = 100# Max idle time for jetty threads (in millis). When a thread exceeds# its idle time it will be terminated.# ducc.driver.jetty.thread.idletime = 60000# Extra JVM args to be appended to any user-supplied "process_jvm_args"# Dynamic: changes to this property immediately affect new submitted work# ducc.process.jvm.args=-XX:+HeapDumpOnOutOfMemoryError# --------------------------------------------------------------# name: ducc.jd.communications.scheme# purpose: specify communications scheme between JD and JPs# choices: [http,https] default=https# change: effective immediately for new jobsducc.jd.communications.scheme=https# --------------------------------------------------------------# name: ducc.jd.error.handler.class# purpose: specify error handler# default: org.apache.uima.ducc.ErrorHandler# change: effective immediately for new jobs# details: The error handler class is employed when work items fail or time-out in order# to determine what to do next in three dimensions:# job kill or continue, process kill or continue, work item kill or continue.ducc.jd.error.handler.class = org.apache.uima.ducc.ErrorHandler# --------------------------------------------------------------# name: ducc.jd.error.handler.args# purpose: configure error handler# choices: max_job_errors=<e> max_timeout_retrys_per_workitem=<r># change: effective immediately for new jobs# details: The error handler args passed to the error handler class (see above).# These values, if any, are combined with any specified by the user.# Individual user specified --driver_exception_handler_arguments <args># prevail.ducc.jd.error.handler.args = max_job_errors=15 max_timeout_retrys_per_workitem=0# +==================================================================================================+# | Service Manager |# +==================================================================================================+# This is the name of the pluggable java class used to implement the Service Manager.ducc.sm.configuration.class=org.apache.uima.ducc.sm.config.ServiceManagerConfiguration# This is the JMS endpoint name used for API messages received by the Service Manager.ducc.sm.api.endpoint=ducc.sm.api# This is the JMS message type used for API messages received by the Service Manager.ducc.sm.api.endpoint.type=queue# This is the JMS endpoint name used for state messages sent by the Service Manager.ducc.sm.state.update.endpoint=ducc.sm.state# This is the JMS message type used for state messages sent by the Service Manager.ducc.sm.state.update.endpoint.type=topic# Default pinger# This is the name of the default UIMA-AS ping/monitor class. The default class issues# get-meta to a service and uses JMX to fetch queue statistics for presentation in# the Web Server.# This name is either:# - The fully qualified name of the class to use as the default UIMA-AS pinger. It may# be necessary to include the class or jar file in the classpath used to start the SM.# (The recommended way to do this is add an entry to the ducc.local.jars property# in ducc.properties.# - The name of a pinger registration file. This is the recommended way to# provide installation-customized pingers. In short, it resides in ducc.properties# and contains the full set of ping-related properties needed to run a pinger.ducc.sm.default.monitor.class = org.apache.uima.ducc.sm.UimaAsPing# This is the maximum number of consecutive failures of service instance initialization# permitted before DUCC stops creating new instances. When this cap is hit the SM# will disable autostart for the service. It may be overridden by the service# registration’s instance_failures_limit parameter.ducc.sm.instance.failure.max 5# backward compatibilityducc.sm.instance.failure.limit ${ducc.sm.instance.failure.max}# This specifies a window of time in minutes over which some number of service instance# failures are tolerated. If the maximum number of tolerated failures is# exceeded within this time window the Service Manager ceases to restart# instances automatically. The maximum tolerated failures is defined in# ducc.sm.instance.failure.max.# This may be overridden by individual service pingers using the registration# property instance_failures_window.ducc.sm.instance.failure.window 30# max consecutive instance init failures before we stop trying to start thingsducc.sm.init.failure.limit 1# This is the time, in milliseconds, between pings by the Service Manager# to each known, running service.ducc.sm.meta.ping.rate = 60000# This is the number of consecutive pings that may be missed before a# service is considered unavailable.ducc.sm.meta.ping.stability = 10# This is the time in milliseconds the SM waits for a response to a ping. If the service does# not respond within this time the ping is accounted for as a "missed" ping.ducc.sm.meta.ping.timeout = 15000# This is the HTTP port used by the Service Manager to field requests from the CLI / API.# *****# NOTE: for backward CLI / API compatibility (2.2.0 and before) this port is the same as# ducc.orchestrator.http.port. This entry can otherwise be deleted post-2.2.0 as it is no# longer used by the current CLI / API.# *****ducc.sm.http.port=${ducc.orchestrator.http.port}# This is the node where the Service Manager runs. It MUST be configured as part of DUCC# setup. The ducc_post_install procedures initialize this to ${ducc.head}ducc.sm.http.node=${ducc.head}# This is the length of time, in milliseconds, that the SM allows a service to remain alive after# all jobs that reference it have exited. If no new job referencing it enters the system before this# time has expired, the SM stops the service.ducc.sm.default.linger=300000# +==================================================================================================+# | Orchestrator |# +==================================================================================================+# This is the name of the pluggable java class used to implement the DUCC Orchestrator.ducc.orchestrator.configuration.class=org.apache.uima.ducc.orchestrator.config.OrchestratorConfiguration# This indicates the level of recovery to be taken on restarting a# system. There are three levels of startup:# [cold] All reservations are canceled, all currently running# jobs (if any) are terminated. All services are terminated. The# system starts with no jobs, reservations, or services active.# [warm] All active work is continued.#------------------------------------------------------------------------------# cold, // Recover: All active are forced to Completed JD host: employ new# warm, // Recover: All Jobs+Services+Reservations (default) JD host: employ currentducc.orchestrator.start.type=warm#------------------------------------------------------------------------------# This is the name of the JMS endpoint through which the Orchestrator broadcasts its# state messages. These messages include full job information and can be relatively# large, though they are now compressed.ducc.orchestrator.state.update.endpoint=ducc.orchestrator.state# This is the JMS endpoint type used for the state messages sent by the Orchestrator.ducc.orchestrator.state.update.endpoint.type=topic# The interval in milliseconds between Orchestrator publications of its state.ducc.orchestrator.state.publish.rate=10000#------------------------------------------------------------------------------# How long between between maintenance cycles (in milliseconds)# Each maintenance cycle the orchestrator removes obsolete JD queues (MqReaper)# and performs health related activities (HealthMonitor) including: capping JPs# for a Jobs that have too many initialization failures and terminating Jobs whose# JDs have failed.ducc.orchestrator.maintenance.rate=60000#------------------------------------------------------------------------------# This is the HTTP port used by the Orchestrator to field requests from the CLI / API.ducc.orchestrator.http.port=19988# Node where OR is running. This is needed by CLI to compose a URL to access OR jetty server.# This is the node where the Orchestrator runs. It MUST be configured as part of DUCC# setup. The ducc_post_install procedures initialize this to ${ducc.head}ducc.orchestrator.http.node=${ducc.head}#------------------------------------------------------------------------------# Specify if reserving an entire machine is allowed# Allowing could be a bad idea when a cluster has very few, very large machines.ducc.orchestrator.unmanaged.reservations.accepted=true#------------------------------------------------------------------------------# This is the name of the JMS endpoint through which the daemons broadcast state changesducc.daemons.state.change.endpoint=ducc.daemons.state.change# This is the JMS endpoint type used for the state change messages sent by the daemons.ducc.daemons.state.change.endpoint.type=queue# +==================================================================================================+# | Resource Manager (aka Scheduler) |# +==================================================================================================+# This is the name of the pluggable java class used to implement the DUCC Resource# Manager.ducc.rm.configuration.class=org.apache.uima.ducc.rm.config.ResourceManagerConfiguration# This is the name of the JMS endpoint through which the Resource Manager broadcasts its# state.ducc.rm.state.update.endpoint=ducc.rm.state# This is the JMS endpoint type used for state messages sent by the Resource Manager.ducc.rm.state.update.endpoint.type=topic# This specifies the frequency of RM schedules, relative to the number of Orchestrator publications.# If the value is set to 1, RM runs and publishes a schedule immediately on receipt of OR state.# If set to some number N, RM runs a schedule after receipt of every N Orchestrator publications.ducc.rm.state.publish.ratio = 1# This specifies the maximum non-preemptable shares any user may be awarded, in GB. If not configured,# there is no maximum enforced. This can be overridden on a per-user basis in the user registry.#ducc.rm.global_allotment = 360# The share quantum is the smallest amount of RAM that is schedulable for jobs, in GB.# Jobs are scheduled based entirely on their memory requirements. Memory is allocated in# multiples of the share quantum.ducc.rm.share.quantum = 1# The component that implements the scheduling algorithm is pluggable. This specifies the# name of that class.ducc.rm.scheduler = org.apache.uima.ducc.rm.scheduler.NodepoolScheduler# File defining the scheduler classes - found in DUCC_HOME/resourcesducc.rm.class.definitions = ducc.classes# File defining the user registry. Optional, need not exist. Found in DUCC_HOME/resources.# The registry is used only to override the global allotments. The registry entries may also# be placed in the ducc.classes file if desired.ducc.rm.user.registry = ducc.users# default memory, in GB, if not specifiedducc.rm.default.memory = 4# Number of node metrics heartbeats to wait for before rm starts up.# During DUCC initialization the Resource Manager must wait some period of time for# all the nodes in the cluster to check-in via their "heartbeats". If the RM were to start# scheduling too soon there would be a period of significant "churn" as the perceived cluster# configurations changes rapidly. As well, it would be impossible to recover work in a warm# or hot start if the affected nodes had not yet checked in.# The init.stability property indicates how many heartbeat intervals the RM must wait before# it starts scheduling after initialization.ducc.rm.init.stability = 2# Number of missed node metrics updates to consider node down.# The RM receives regular "heartbeats" from the DUCC agents in order to know what# nodes are available for scheduling. The node.stability property configures the number of# consecutive heartbeats that may be missed before the Resource Manager considers the# node to be inoperative.# If a node becomes inoperative, the Resource Manager deallocates all processes on that# node and attempts to reallocate them on other nodes. The node is marked offline and is# unusable until its heartbeats start up again.# The default configuration declares the agent heartbeats to occur at 1 minute intervals.# Therefore heartbeats must be missed for five minutes before the Resource Manager takes# corrective action.ducc.rm.node.stability = 5# Which policy to use when shrinking/evicting shares - alternatively, SHRINK_BY_MACHINE.# The eviction.policy is a heuristic to choose which processes of a job to preempt because of# competition from other jobs.# The SHRINK_BY_INVESTMENT (default) policy attempts to preempt processes such that the# least amount of work is lost. It chooses candidates for eviction in order of:# - Processes still initializing, with the smallest time spent in the initializing step.# - Processes whose currently active work items have been executing for the shortest time.# The SHRINK_BY_MACHINE policy attempts to preempt processes so as to minimize# fragmentation on machines with large memories that can contain multiple job processes.# No consideration of execution time or initialization time is made.ducc.rm.eviction.policy = SHRINK_BY_INVESTMENT# Max nodes to initially allocate until init is complete.# The type of jobs supported by DUCC generally have very long and often fragile# initialization periods. Errors in the applications and other problems such is missing or# errant services can cause processes to fail during this phase.# To avoid preempting running jobs and allocating a large number of resources to jobs only# to fail during initialization, the Resource Manager schedules a small number of processes# until it is determined that the initialization phase will succeed.# The initialization.cap determines the maximum number of processes allocated to a job# until at least one process successfully initializes. Once any process initializes the Resource# Manager will proceed to allocate the job its full fair share of processes.# The initialization cap can be overridden on a class basis by configuration via ducc.classes.ducc.rm.initialization.cap = 1# When true, jobs expand not all at once after init, but a bit slower, doubling each epoch# until max fair-share is set. If false, jobs increase immediately to their fair share,# at the cost of mass evictions.# Expand.by.doubling can be overridden on a class basis by configuration via ducc.classes.ducc.rm.expand.by.doubling = true# Predict when a job will end and avoid expanding if not needed.# Because initialization time may be very long, it may be the case that a job that might be# eligible for expansion will be able to complete in the currently assigned shares before any# new processes are able to complete their initialization. In this case expansion results in# waste of resources and potential eviction of processes that need not be evicted.# The Resource Manager monitors the rate of task completion and attempts to predict the# maximum number of processes that will be needed at a time in the future based on the# known process initialization time. If it is determined that expansion is unnecessary then it# is not done for the job.# Prediction can be overridden on a class basis by configuration via ducc.classes.ducc.rm.prediction = true# Add this fudge factor (milliseconds) to the expansion target when using prediction.# When ducc.rm.prediction is enabled, the known initialization time of a job’s processes plus# some "fudge" factor is used to predict the number of future resources needed. The "fudge"# is specified in milliseconds.# The default "fudge" is very conservative. Experience and site policy should be used to set a# more practical number.# Prediction.fudge can be overridden on a class basis by configuration via ducc.classes.ducc.rm.prediction.fudge = 120000# What is minimum number of processes for a job before we do defrag? If a job has less than# this amount RM may attempt defragmentation to bring the processes up to this value.# If enabled, limited defragmentation of resources is performed by the Resource Manager to# create sufficient space to schedule work that has insufficient resources (new jobs, for# example.). The term "insufficient" is defined as "needing more processes than the# defragmentation # threshold, but currently having fewer processes than the defragmentation# threshold." These are called "needy" jobs. Additionally, the Resource Manager# will never evict processes from ‘‘needy’’ jobs for the purpose of defragmentation.# This property allows installations to customize the value used to determine if a# job is "needy". Jobs with fewer processes than this are potentially needed, and# jobs with more processes are never needy.ducc.rm.fragmentation.threshold = 8# This JMS endpoint used for RM administrative requests.ducc.rm.admin.endpoint = ducc.rm.admin.channel# This is the JMS endpoint type used for RM administrative requests.ducc.rm.admin.endpoint.type = queue# This JMS endpoint used for RM administrative requests.ducc.rm.via.or.admin.endpoint = ducc.rm.via.or.admin.channel# This is the JMS endpoint type used for RM administrative requests.ducc.rm.via.or.admin.endpoint.type = queue# Unmanaged Reservations are usually assigned to machines whose size exactly matches the# requested size, after rounding up to a multiple of the node pool’s quantum.# When this property is positive, machines up to this many GB larger than the rounded up# size will be considered.ducc.rm.reserve_overage = 0# +==================================================================================================+# | Agents |# +==================================================================================================+# This is the name of the pluggable java class used to implement the DUCC Agents.ducc.agent.configuration.class=org.apache.uima.ducc.agent.config.AgentConfiguration# This is the JMS endpoint through which agents receive state from the Process Manager.ducc.agent.request.endpoint=ducc.agent# This is the JMS endpoint type used for state messages sent by the Process Manager.ducc.agent.request.endpoint.type=topic# This is the JMS endpoint used to communicate# from the managed process to the Agent (Job Process).ducc.agent.managed.process.state.update.endpoint=ducc.managed.process.state.update# This is the JMS endpoint type used to communicate# from the managed process (Job Process) to the Agent.ducc.agent.managed.process.state.update.endpoint.type=socket# Endpoint parameters which are transport specific.# For socket transport params are:# - transferExchange=true - include Camel Exchange wrapper in a message# - synch=false - use socket transport for one-way messaging (no replies neeeded)ducc.agent.managed.process.state.update.endpoint.params=transferExchange=true&sync=false# ***** Note: the Resource Manager uses the data in the node metrics for scheduling.# The interval in milliseconds between node metric publications.# Every agent publishes its updates at this rate. On large clusters, a high rate (small# interval) can be a burden on the network.ducc.agent.node.metrics.publish.rate=30000# This is the JMS endpoint used to send node metrics updates to listeners. Listeners# are usually the Resource Manager and Web Server. These messages serve as node# "heartbeats". As well, the node metrics heartbeats contain the amount of RAM on the node# and the number of processors.ducc.agent.node.metrics.endpoint=ducc.node.metrics# This is the JMS endpoint type used to send node metrics updates from the agents.ducc.agent.node.metrics.endpoint.type=topic# The interval in milliseconds between node inventory publications.# If the inventory has not changed since the last update the agent bypasses sending the# update, up to a maximum of ducc.agent.node.inventory.publish.rate.skip times.ducc.agent.node.inventory.publish.rate=10000# This is the number of times the agent will bypass publishing its node inventory if the# inventory has not changed.ducc.agent.node.inventory.publish.rate.skip=3# This is the JMS endpoint used to send node inventory messages to listeners. Listeners are# usually the Orchestrator and Web Server. Information in these messages include a map of# processes being managed on the node.ducc.agent.node.inventory.endpoint=ducc.node.inventory# This is the JMS endpoint type used to send node inventory updates from the agents.ducc.agent.node.inventory.endpoint.type=topic# ducc.agent.launcher.thread.pool.size - Deprecated#ducc.agent.launcher.thread.pool.size=10# enable/disable use of ducc_ling# ducc.agent.launcher.use.ducc_spawn: true, use ducc_ling. Default: falseducc.agent.launcher.use.ducc_spawn=true# Specify location of ducc_ling in the filesystem.# This property specifies the full path to the ducc_ling utility. During installation ducc_ling# is normally moved to local disk and given setuid-root privileges. Use this property to tell# the DUCC agents the location of the installed ducc_ling. The default location is within# an architecture dependent subdiretory of DUCC_HOME/admin.# The arcitecture is derived from the JRE property os.arch. During DUCC installation# the ducc_ling utility is compiled for the architecture of the host where DUCC is installed.# In heterogeneous clusters, the system administrator should run the utility build_duccling# once on a machine of each architecture to insure this utility gets correctly installed.ducc.agent.launcher.ducc_spawn_path=${DUCC_HOME}/admin/${os.arch}/ducc_ling# Max amount of time (in millis) agent allows the process to stop before issuing kill -9.# This property specifies the time, in milliseconds, the agent should wait before forcibly# terminating a job process (JP) after an attempted graceful shutdown. If the child process# does not terminate in the specified time, it is forcibly terminated with kill -9.# This type of stop can occur because of preemption or system shutdown.ducc.agent.launcher.process.stop.timeout=60000# Max time in millis allowed for AE initialization. Default 2 hours 7200000. - Deprecated#ducc.agent.launcher.process.init.timeout=7200000# Exclude the following user ids while detecting rogue processes# The DUCC Agents scan nodes for processes that should not be running; for example,# a job may have left a ’rogue’ process alive when it exits, or a user may log in to a node# unexpectedly. These processes are reported to the administrators via the webserver for# possible action.# This configuration parameter enumerates userids which are ignored by the rogue-process scan.# default = root,posstfix,ntp,nobody,daemon,100ducc.agent.rogue.process.user.exclusion.filter=# Max UID reserved by OS. This is used to detect rogue processes and to report# available memory on a node.# The ducc.agent.node.metrics.sys.uid.max property is droped in favor of# ducc.agent.rogue.process.sys.user.max, which seems more descriptive## ducc.agent.node.metrics.sys.uid.max=500ducc.agent.rogue.process.sys.uid.max=500# Exclude the following processes while detecting rogue processes# The DUCC Agents scan nodes for processes that should not be running; for example,# a job may have left a ’rogue’ process alive when it exits, or a user may log in to a node# unexpectedly. These processes are reported to the administrators via the webserver for# possible action.# This configuration parameter enumerates processes by name which are ignored by the# rogue process detector.# default = sshd:,-bash,-sh,/bin/sh,/bin/bash,grep,psducc.agent.rogue.process.exclusion.filter=sshd:,-bash,-sh,/bin/sh,/bin/bash,grep,ps# Fudge Factor (in terms of percantage) that agent uses to multiply a share size when# determining if a JP exceeds its alloted memory, which is calculated as follows# (fudge factor/100)*share size + share size. If this number exceeds JPs RSS, the agent# kills the process.# The DUCC agent monitors the size of the resident memory of its spawned processes. If a# process exceeds its declared memory size by any significant amount it is terminated and# a ShareSizeExceeded message is sent. The Job Driver counts this towards the maximum# errors for the job and will eventually terminate the job if excessive such errors occur.# This property defines the percentage over the declared memory size that a process is# allowed to grow to before being terminated.# To disable this feature, set the value to -1.ducc.agent.share.size.fudge.factor=5# Enable/Disable CGroup support.# If CGroups are not installed on a specific machine, this is ignored.# With CGroups the RSS for a managed process (plus any children processes it may spawn) is# limited to the allocated share size. Additional memory use goes to swap space. DUCC# monitors and limits swap use to the same proportion of total swap space as allocated# share size is to total RAM. If a process exceeds its allowed swap space it is terminated# and a ShareSizeExceeded message is sent to the Job Driver.# Nodes not using CGroups fall back to the ducc.agent.share.size.fudge.factor.ducc.agent.launcher.cgroups.enable=true# Define location of cgroups utils like cgexec. For mixed clusters with different# flavors of unix, the utilities may be in different places. In such case, add a# a comma separated list of paths like this:# ducc.agent.launcher.cgroups.utils.dir=/usr/bin,<OS 1 path>,<OS 2 path>ducc.agent.launcher.cgroups.utils.dir=/usr/bin,/bin# Set cgroup memory.swappinessducc.agent.launcher.cgroups.swappiness=10# Number of retries to use when cgcreate failsducc.agent.launcher.cgroups.max.retry.count=1# Amount by which to increase delay (in msecs) between each retry# Defines a delay factor in millis an agent will use to determine how long it# should sleep between cgroup create retries. Each time cgcreate fails# an agent will increment the delay by adding the delay factor to a previous# delay. If the delay factor is 2000, on first cgcreate failure an agent will# wait 2000 ms, on second failure the wait time will be 4000, on third 6000, and# so on.ducc.agent.launcher.cgroups.retry.delay.factor=2000# Exclusion file to enable node based exclusion for cgroups and aps# syntax: <node>=cgroups,ap# the above will exclude node from using cgroups and/or prevent deployment of APsducc.agent.exclusion.file=${DUCC_HOME}/resources/exclusion.nodes# Define script which will collect total swap used by a given process. This# script is launched by an agent via duccling and running as the owner# of the process.ducc.agent.swap.usage.script=${DUCC_HOME}/admin/ducc_get_process_swap_usage.sh# Uncomment the following line to support auto reaping of rogue processes by Ducc’s Agent# ducc.agent.rogue.process.reaper.script=${DUCC_HOME}/admin/ducc_reap_rogues.sh# +==================================================================================================+# | Process Manager |# +==================================================================================================+# This is the name of the pluggable java class used to implement the DUCC Process Manager.ducc.pm.configuration.class=org.apache.uima.ducc.pm.config.ProcessManagerConfiguration# This is the endpoint through which process manager receive state from the Orchestrator.ducc.pm.request.endpoint=ducc.pm# This is the JMS endpoint type used for state messages sent by the Orchestrator.ducc.pm.request.endpoint.type=queue# This is the endpoint through which process manager sends its heartbeat. The main receiver# is the Web Server for it’s daemon status page.ducc.pm.state.update.endpoint=ducc.pm.state# This is the JMS endpoint type used for process manager heartbeats. The primary receiver# is the Web Server for its daemon status page.ducc.pm.state.update.endpoint.type=topic# The interval in milliseconds between process manager heartbeat publications.ducc.pm.state.publish.rate=15000# +==================================================================================================+# | Job Process |# +==================================================================================================+# This is the name of the pluggable java class that implements# the shell for Agent launched user processes.ducc.uima-as.configuration.class=org.apache.uima.ducc.transport.configuration.jp.JobProcessConfigurationducc.job-process.configuration.class=org.apache.uima.ducc.transport.configuration.jp.JobProcessConfigurationducc.service.configuration.class=org.apache.uima.ducc.transport.configuration.service.ServiceConfiguration# This is the endpoint through which job processes (JPs) receive messages from the Agents.ducc.uima-as.endpoint=ducc.job.managed.service# This is the JMS endpoint type used for messages sent to the JPs from the Agents.ducc.uima-as.endpoint.type=socket# Endpoint parameters which are transport specific.# For socket transport params are:# - transferExchange=true - include Camel Exchange wrapper in a message# - synch=false - use socket transport for one-way messaging (no replies neeeded)ducc.uima-as.endpoint.params=transferExchange=true&sync=false# saxon8.jar - Saxon is an XSLT and XQuery processor. It is used by UIMA-AS# when deploying a service.ducc.uima-as.saxon.jar.path=file:${DUCC_HOME}/apache-uima/saxon/saxon8.jar# dd2spring.xsl - contains a set of rules used when transforming# UIMA-AS deployment descriptor into SpringFramework’s# context file used to deploy UIMA-AS based service.ducc.uima-as.dd2spring.xsl.path=${DUCC_HOME}/apache-uima/bin/dd2spring.xsl# Maximum amount of time to wait for a response from the JD. This value# is used by the JP when sending requests to the JD.ducc.process.request.timeout=30000# Define process container class for DD jobs to instantiate and invoke via reflection.# The container provides classpath isolation for user defined analytics.# The container is instantiated with classes from a System classloader.ducc.process.uima.as.container.class = org.apache.uima.ducc.user.jp.UimaASProcessContainer# Define process container class for non-DD jobs to instantiate and invoke via reflection.# The container provides classpath isolation for user defined analytics.# The container is instantiated with classes from a System classloader.ducc.process.uima.container.class = org.apache.uima.ducc.user.jp.UimaProcessContainer# Define the sleep time (millis) for JP to use when JD sends empty CAS. In this case the# JD’s CR has processed its collection. The JP threads need to slow down sending# requestsducc.process.thread.sleep.time=60000# Custom Flow Controller to use for Ducc Job Processes that don’t provide a process_DD descriptorducc.flow-controller.specifier=org.apache.uima.ducc.FlowController# +==================================================================================================+# | Database |# +==================================================================================================+# Name of the database host - initially disabled until database is created.# Overridden in site.ducc.properties by ducc_post_install or db_create.# This is the name of the host where the database is run. It usually defaults to the# same host as the ducc.head. Those knowledgable of the database can install the# database elsewhere. Use this parameter to specify that location.# To disable use of the database, set this parameter to the string --disabled--ducc.database.host = --disabled--# Database JMX host. Default is to allow only local JMX access. Specify the real name for remote access.ducc.database.jmx.host = localhost# Database JMX port.ducc.database.jmx.port = 7199#-----------------------------------# DATABASE MEMORY TUNING# WARNING: if you’re not sure what these do you should probably not change them as incorrect# values can adversly affect the database, the database node, or both.# Given that. If you’re running on a mostly small system, e.g. 8GB or less, probably you# should set ducc.database.mem.heap to 1 or 2 GB and ducc.database.mem.new to 100M## By default we allow cassandra to calculate these for us.## IMPORTANT: if you set one of these you MUST set both, or cassandra will refuse to start.#-----------------------------------# Database xmx. If not set, cassandra will calculate it for you.# This is the value used to set {\em Xmx and Xms} when the database starts. The# Cassandra database makes an attempt to determine the best value of this. The# default is one-half of real memory, up to a maximum of 8G. It is recommended that# the default be used. However, small installations may reduce this to as little# as 512M. Note that both Xmx and Xms are set.#ducc.database.mem.heap = 4G# Database setting for ’young’ generation. If not set, cassandra will calculate it for you.#ducc.database.mem.new = 100M#-----------------------------------k# END OF DATABASE MEMORY TUNING#-----------------------------------# This class implementes the persistence interface for the services registry#ducc.service.persistence.impl = org.apache.uima.ducc.database.StateServicesDbducc.service.persistence.impl = org.apache.uima.ducc.common.persistence.services.StateServices# This class implements the persistence interface for Job, Reservation, Service, and AP instances, plus# the Orchestrator checkpoint.#ducc.job.history.impl = org.apache.uima.ducc.database.HistoryManagerDbducc.job.history.impl = org.apache.uima.ducc.transport.event.common.history.HistoryPersistenceManager#ducc.rm.persistence.impl = org.apache.uima.ducc.database.RmStatePersistenceducc.rm.persistence.impl = org.apache.uima.ducc.common.persistence.rm.NullRmStatePersistence# end database things -------------------------------------------------------------------------------

13.6 Resource Manager Configuration: Classes and Nodepools

The class configuration file is used by the Resource Manager configures the rules used for job scheduling. See the Resource
Manager chapter for a detailed description of the DUCC scheduler, scheduling classes, and how classes are used to configure
the scheduling process.

The scheduler configuration file is specified in ducc.properties. The default name is ducc.classes and is specified by the
property ducc.rm.class.definitions.

13.6.1 Nodepools

Overview

A nodepool is a grouping of a subset of the physical nodes to allow differing scheduling policies to be applied to different
nodes in the system. Some typical nodepool groupings might include:

1.

Group Intel and Power nodes separately so that users may submit jobs that run only in Intel architecture, or
only Power, or “don’t care”.

2.

Designate a group of nodes with large locally attached disks such that users can run jobs that require those
disks.

3.

Designate a specific set of nodes with specialized hardware such as high-speed network, such that jobs can be
scheduled to run only on those nodes.

A Nodepool is a subset of some larger collection of nodes. Nodepools themselves may be further subdivided. Nodepools may
not overlap: every node belongs to exactly one nodepool. During system start-up the consistency of nodepool definition is
checked and the system will refuse to start if the configuration is incorrect.

NOTE: The administrative command check_ducc -c may be used to verify and validate you class configration before
attemping to start DUCC. check_ducc -cv may be used to additionally “pretty-print” the ducc.classes configuration to the
console to revel class nesting and inheritance.

For example, the diagram below is an abstract representation of all the nodes in a system. There are five nodepools
defined:

Nodepool “NpAllOfThem” is subdivided into three pools, NP1, NP2, and NP3. All the nodes not contained in
NP1, NP2, and NP3 belong to the pool called “NpAllOfThem”.

Nodepool NP1 is not further subdivided.

Nodepool NP2 is not further subdivided.

Nodepool NP3 is further subdivided to form NP4. All nodes within NP3 but not in NP4 are contained in NP3.

Nodepool NP4 is not further subdivided.

Figure 13.1: Nodepool Example

In the figure below the Nodepools are incorrectly defined for two reasons:

1.

NP1 and NP2 overlap.

2.

NP4 overlaps both nodepool “NpAllOfThem” and NP3.

Figure 13.2: Nodepools: Overlapping Pools are Incorrect

Multiple “top-level” nodepools are allowed. A “top-level” nodepool has no containing pool. Multiple top-level pools logically
divide a cluster of machines into multiple independent clusters from the standpoint of the scheduler. Work scheduled over one
pool in no way affects work scheduled over the other pool. The figure below shows an abstract nodepool configuration with
two top-level nodepools, “Top-NP1” and “Top-NP2”.

Figure 13.3: Nodepools: Multiple top-level Nodepools

Scheduling considerations

A primary goal of the scheduler is to insure that no resources are left idle if there is pending work that is able to use those
resources. Therefore, work scheduled to a class defined over a specific nodepool (say, NpAllOfThem), may be
scheduled on nodes in any of the nodepools contained within NpAllOfThem. If work defined over a subpool (such
as NP1) arrives, processes on nodes in NP1 that were scheduled for NpAllOfThem are considered squatters
and are the most likely candidates for eviction. (Processes assigned to their proper nodepools are considered
residents and are evicted only after all squatters have been evicted.) The scheduler strives to avoid creating
squatters.

Because non-preemptable allocations can’t be preempted, work submitted to a class implementing one of the
non-preemptable policies (FIXED or RESERVE) are never allowed to “squat” in other nodepools and are only scheduled on
nodes in their proper nodepool.

In the case of multiple top-level nodepools: these nodepools and their sub-pools form independent scheduling groups.
Specifically,

Fair-share allocations over any nodepool in one top-level pool do NOT affect the fair-share allocations for jobs
in any other top-level nodepool. Top-level nodepools define independently scheduled of resources within a single
DUCC cluster.

Work submitted to classes under one top-level nodepool do NOT get expanded to nodes under another top-level
nodepool, even is there is sufficient capacity.

Most installations will want to assign the majority of nodes to a single top-level nodepool (or its subpools), using other
top-level pools for nodes that cannot be shared with other work.

Configuration

At least one nodepool definition is required. This nodepool need not have any subpools or node definitions. The first top-level
nodepool is considered the “default” nodepool. Any node not named specifically in one of the node files which checks in with
DUCC is assigned to this first, default nodepool.

Thus, if only one nodepool is defined with no other attributes, all nodes are assigned to that pool.

A nodepool definition consists of the token “Nodepool” followed by the name of the nodepool, followed by a
block delimited with “curly” braces { and }. This block contains the attributes of the nodepool as key/value
pairs. Lineneds are ignored. A semicolon “;” may optionally be used to delimit key/value pairs for readability,
and an equals sign “=” may optionally be used to delimit keys from values, also just for readability. See the
below.

The attributes of a Nodepool are:

domain

This is valid only in the “default” (first) nodepool. Any node in any nodefile which does not have a domain,
and any node which checks in to the Resource Manager without a domain name is assigned this domain name
in order that the scheduler may deal entirely with full-qualified node names.

If no domain is specified, DUCC will attempt to guess the domain based on the domain name returned on the
node where the Resource Manager resides.

nodefile

This is the name of a file containing the names of the nodes which are members of this nodepool.

parent

This is used to indicate which nodepool is the logical parent. Any nodepool without a parent is considered
a top-level nodepool.

The following example defines six nodepools,

1.

A top-level nodepool called “–default–”. All nodes not named in any nodefile are assigned to this nodepool.

2.

A top-level nodepool called “jobdriver”, consisting of the nodes named in the file jobdriver.nodes.

3.

A subpool of “–default–” called “intel”, consisting of the nodes named in intel.nodes.

4.

A subpool of “–default–” called “power”, consisting of the nodes named in the file power.nodes.

5.

A subpool of “intel” called “nightly-test”, consisting of the nodes named in nightly-test.nodes.

6.

And a subpool of “power” called “timing-p7”, consisting of the nodes named in timing-p7.nodes.

13.6.2 Class Definitions

Scheduler classes are defined in the same simple block language as nodepools.

A simple inheritance (or “template”) scheme is supported for classes. Any class may be configured to “derive” from any other
class. In this case, the child class acquires all the attributes of the parent class, any of which may be selectively overridden.
Multiple inheritance is not supported but nested inheritance is; that is, class A may inherit from class B
which inherits from class C and so on. In this way, generalized templates for the site’s class structure may be
defined.

The general form of a class definition consists of the keyword Class, followed by the name of the class, and then optionally by
the name of a “parent” class whose characteristics it inherits. Following the name (and optionally parent class name) are the
attributes of the class, also within a { block } as for nodepools, and with lines and key/value pairs optionally delimited by “;”
and “=”, respectively. See the sample below.

The attributes defined for classes are:

abstract

If specified, this indicates this class is a template ONLY. It is used as a model for other classes. Values are
“true” or “false”. The default is “false”. This class is never passed to the scheduler and may not be referenced
by jobs.

debug

FAIR_SHARE only. This specifies the name of a class to substitute for jobs submitted for debug. For example, if
class normal specifies

debug = fixed

then any job submitted to this class with debugging requested is actually scheduled in class fixed. (For example, one
probably does not want a debugging job scheduled as FAIR_SHARE and possibly preempted, preferring the
non-preemptable class fixed.

default

This specifies the class to be used as the default class for work submission if no class is explicitly given. Only one
class of type FAIR_SHARE may contain this designation, in which case it names the default FAIR_SHARE class. Only
one class of type FIXED_SHARE or RESERVE may contain this designation, in which case it names the default class
to use for reservations (Note that either FIXED_SHARE or RESERVE scheduling policies are valid for
reservations.)

expand-by-doubling

FAIR_SHARE only. If “true”, and the initialization-cap is set, then after any process has
initialized, the job will expand to its maximum allowable shares by doubling in size each scheduling
cycle.

FAIR_SHARE and FIXED_SHARE only. This is the largest number of FIXED-SHARE, non-preemptable
shares any single job may be assigned.

Omit this property, or set it to 0 to disable the cap.

g

prediction-fudge

FAIR_SHARE only. When the scheduler is considering expanding the number of processes for a job
it tries to determine if the job may complete before those processes are allocated and initialized. The
prediction-fudge adds some amount of time (in milliseconds) to the projected completion time. This allows
installations to prevent jobs from expanding when they were otherwise going to end in a few minutes
anyway.

Jobs for this class are assigned to nodes in this nodepool. The value must be the name of one of the configured
nodepools.

policy

This is the scheduling policy, one of FAIR_SHARE, FIXED_SHARE, or RESERVE. This attribute is required (there
is no default).

priority

This is the scheduling priority for jobs in this class.

weight

FAIR_SHARE only. This is the fair-share weight for jobs in this class.

The following figure illustrates a representative class configuration for a large cluster, consisting of mixed Intel and Power
nodes. This class definition assumes the nodepool configuration shown above. FAIR_SHARE, FIXED_SHARE,
and RESERVE classes are defined over each machine architecture, Intel and Power, and over the combined
pool.

13.6.3 Validation

The administrative command, check_ducc may be used to validate a configuration, with the -c and v options. This reads the
entire configuration and nodefiles, validates consistency of the definitions and insures the nodepools do not
overlap.

The start_ducc command always runs full validation, and if the configuration is found to be incorrect, the cluster is not
started.

Configuration checking is done internally by the DUCC java utility org.apache.uima.ducc.common.NodeConfiguration.
This utility contains a public API as described in the Javadoc. It may be invoked from the command line as
follows:

Pretty-print the compiled configuration to stdout. This illustrates nodepool nesting, and shows the
fully-completed scheduling classes after inheritance.

-v nodefile

This should be the master nodelist used to start DUCC. This is assumed to be constructed to reflect
the nodepool organization as described here. If provided, the nodepools are validated and checked for overlaps.

configfile

This is the name of the file containing the configuration.

13.7 Ducc Node Definitions

The DUCC node definitions are specified by default in the file ducc.nodes.

The DUCC node list is used to configure the nodes used to run jobs and assign reservations. When DUCC is started, the
nodelist is read an a DUCC Agent is started on every node in the list.

The node list can be composed of multiple node lists to assist organization of the DUCC cluster. All the administrative
commands operate upon node lists. By carefully organized these lists it is possible to administer portions of a cluster
independently.

In particular, it is highly recommended that the nodelists reflect the nodepool structure. In this way, the configuration used
to start DUCC is guaranteed to match the nodeppool definitions.

Several types of records are permitted in nodelists:

Comments

A comment starts with the symbol “#”. All text on the line following this symbol is ignored.

import

If a line starts with the symbol import, the next symbol on that line is expected to be the name of another
node list. This permits the DUCC cluster’s nodes to be configured in a structured manner.

For instance, the file ducc.nodes might consist entirely of import statements naming all of the nodepool files.

domain

This must be the first line of the file. If specified, it should name the default domain to be used for all the
nodes in this file, and the nodes named in imported files. If not specified, then during start-up, nodes without
domain names are assigned domain names according to the global domain name specified in the Resource
Manager configuration file, and if none is specified there, the domain name on the host starting DUCC is used.

nodename

This is a single token consisting of the name of a node on which an agent it to be started.

13.8 Ducc User Definitions

As of 2.0.0, the only constraint override is allotment for non-preemptable requests.

The syntax of the user registry is the same as that used in ducc.classes, and in fact, the user registry may be embedded
directly in that file, rather than specified externally.

The registry consists of multiple entries, one for affected user. Any user of the system NOT in the registry acquires the
system defaults.

A user definition consists of the token “User” followed by the id of the user, followed by a block delimited with “curly” braces
{ and }. This block contains the attributes of the nodepool as key/value pairs. Lineneds are ignored. A semicolon “;” may
optionally be used to delimit key/value pairs for readability, and an equals sign “=” may optionally be used to delimit keys
from values, also just for readability.

The attributes of a User entry are:

max-allotment

This overrides the maximum allotment for non-preemptable requests as defined in ducc.properties.
The override may be used to either increase, or decrease the user’s allotment. The units are in gigabytes.

13.9 DUCC Database Integration

As of Version 2.1.0, DUCC uses the Apache Cassandra database instead of the filesystem to manage history and
the service registry. Additionally, the Resource Manager maintains current scheduling and node state in the
database.

13.9.1 Overview

During first-time installation, the ducc_post_install utility randomly generates a (database) super-user password, which is
kept in the protected file DUCC_HOME/resources.private/ducc.private.properties. The utility proceeds to configure the
database and install the schema.

If DUCC is being upgraded, generally ducc_post_install is not used, in which case, again, db_create and db_loader may be
used to convert the older file-based state to the database.

Orchestrator use of the Database

The Orchestrator persists two types of work:

1.

All work history. This includes jobs, reservations, service instances, and arbitrary processes. This history is
what the webserver uses to display details on previously run jobs. Prior to the database, this data was saved
in the DUCC_HOME/history directory.

2.

Checkpoint. On every state change, the Orchestrator saves the state of all running and allocated work
in the system. This is used to recover active allocations when DUCC is started enabling warm-start
of the Orchestrator without losing work. Prior to the database, this data was saved in the file
DUCC_HOME/state/orchestrator.ckpt.

Service Manager use of the Database

The service manager uses the database to store the service registry and all state of active services. Prior to the database, this
data was saved in Java properties files in the directory DUCC_HOME/state/services.

When a service is “unregistered” it is not physically removed from the database. Instead, a bit is set indicating the service is
no long active. These registrations may be recovered if needed by querying the database. Prior to the database, this data was
saved in DUCC_HOME/history/service-registry.